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Energy and the Built Environment
Selected papers presented at the CIB World Building Congres Construction and Society, Brisbane 5-9 May 2013
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Proceedings
Energy and the Built Environment
Papers from the Designated Session Energy and the Built Environment that took place as part of the CIB World Building Congress, Brisbane, Australia, May 2013.
CIB Publication 382
TG66 - Energy and the Built Environment Mandate has expired December 2012
CIB Task Group TG66 focuses on the worldwide / intercontinental comparison / analysis of policies that aim to enhance energy efficiency in buildings in support of decreasing energy consumption, reducing CO2 emissions and/or enhancing the role of renewable energy in the built environment. Such analysis will address: policy objectives, policy instruments and their implementation, actors and lessons learned. It is assumed that such instruments will include: control and regulatory instruments, fiscal instruments and incentives, economic and market based instruments and instruments that stimulate voluntary actions through support and providing information.
CONTENTS Papers A Case Study of the Glen Acres University / Community Partnership to Reduce Energy Consumption in Existing Housing Mark Shaurette, PhD1
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Normative Technical Parameters of Low Energy Buildings Josifas Parasonis
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Cost Effective Energy Savings in Australian Commercial Buildings to 2020 Phil Harrington, Trevor Lee, David Devenish, Phil McLeod
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Cost Effective Energy Savings in Australian Houses to 2020 Tony Marker, Robert Foster, Phil Mcleod
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Life Cycle Energy Analysis of Residential Building Retrofits Incorporating Social Influences Melissa Gaspari
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A Policy Framework for Zero Carbon Buildings in Australia Phil Harrin
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Towards a New Advanced Industry for an Energy Efficient Built Environment Luc Bourdeau, Stefano Carosi
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Feasible Energy Saving Potentials in Renovations for Residential and Service Building Stock Jaakko Vihola1, Juhani Heljo, Antti Kurvinen
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Daylighting Design and Simulation: Ease of use analysis of digital tools for architects Konrad Panitz, Veronica Garcia-Hansen
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A Decision Making System for Selecting Sustainable Technologies for Retail Buildings Zainab Dangana, Wei Pan, Steve Goodhew
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An Evidence Based Online Design Platform: Challenges and Limitations Marina Di Guida , Judit Kimpian, Paola Marrone, Lucia Martincigh, Dejan Mumovic, Craig Robertson
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Non-residential building energy use today and tomorrow Andrew Pollard, Michael Babylon
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Challenges and Opportunities of Low or Zero Carbon Building: Prospects of Business Models
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Wei Pan, Larch Maxey Post-Occupancy Evaluation Studies in a recently Refurbished Office Building: Energy Performance and Employees’ Satisfaction Michelle Agha-Hossein, Sam El-Jouzi, Abbas Elmualim, Judi Ellis, Marylin Williams
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Roadmap enabling ICT to improve energy efficiency in the built environment F. Fouchal, K.A. Ellis, T. M. Hassan, S. K. Firth
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The development of a simple multi-nodal tool to identify performance issues in existing commercial buildings Samantha Hall, David Sparks, Charlie Hargroves, Cheryl Desha, Peter Newman
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Understanding Energy Use in New Zealand’s Non-Residential Buildings Lynda Amitrano, Kay Saville-Smith, Nigel Isaacs & Rob Bishop
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A Case Study of the Glen Acres University / Community Partnership to Reduce Energy Consumption in Existing Housing Mark Shaurette, PhD1 A Case Study of the Glen Acres University / Community Partnership to Reduce Energy Consumption in Existing Housing Existing building stock in the developed world is responsible for approximately 40% of all energy consumption. Replacement of the existing built environment with more efficient structures is not only impractical but also abandons much of the embodied energy already present in the extant materials. As a result, attempts to significantly reduce the operational energy consumption in existing buildings must be based on a combination of energy related retrofit of existing buildings and behavioural changes by the building’s occupants. Due to the common attributes of existing residential buildings, this sector offers large scale opportunity for energy related retrofit. Nevertheless, while the technologies for insulation, climate control, lighting, consumer appliances, and water consumption common to domestic structures are often similar within communities, many complicating factors exist which limit production scale energy retrofit. Unlike new housing construction which has, in many parts of the world, become uniform and systematized, energy related housing retrofit is done on a per house basis and continues to be restricted in scope. The limitations stem from a fragmentation of ownership, a dearth of construction organizations offering whole-house energy retrofit as a primary service, limited funds to advance the process, and housing valuation practices that fail to recognize the value created by energy related retrofits. This paper is a detailed examination of a community-wide energy retrofit project which was financed using stimulus funds from the U.S. government and distributed to a small community adjacent to a major research university. The original concept of market transformation for energy retrofit expected from the program is presented along with the university’s participation in program design, program management, related educational activities, student involvement, and resulting benefits to both the university and the community. In addition, some unexpected challenges which continue to constrain market transformation for energy retrofit are included. Keywords: Energy Conservation, Community Partnership, Market Transformation, Retrofit, Housing, Stimulus Funds
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Assistant Professor; Dept. of Building Construction Management; Purdue University; 401 N. Grant Street, West Lafayette, Indiana, USA, 47907;
[email protected].
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1. Introduction Buildings are tremendous users of electricity, accounting for more than 72% of electricity use in the United States. This contributes 39% of the carbon dioxide (CO2) emissions in the United States per year, more than either the industrial or transportation sector of the economy (The U.S. Green Building Council, 2009). Adopting energy conserving measures and alternative sources of energy production for use in buildings offers vast opportunity toward reaching the national goal of energy independence and reducing climate change. An October 2008 report of the National Science and Technology Council titled Federal Research and Development Agenda for Net-Zero Energy, High Performance Buildings notes the general lack of informational guides and incentives, and the misinformation that exists about energy consumption in buildings. The report recommends effective technology transfer through improved tools and guides, education and training, and market-based building valuation metrics. The basis for this technology transfer would be research and demonstration coupled with private industry activity. This paper describes a program that provides a vehicle for the suggested education and technology transfer specifically targeting residential properties and the conditions encountered in the State of Indiana, USA. The City of Lafayette, located in a small metropolitan area of less than 200,000 residents, was awarded grant funding from the U.S. federal government for approximately 80 energy conserving retrofits in the Glen Acres and Vinton communities through a retrofit ramp-up program. Lafayette administered these funds through the use of staff currently employed under a Comprehensive Neighborhood Revitalization Fund for Glen Acres. The fund for this Neighborhood Stabilization Program (NSP) financed the acquisition of foreclosed properties that are rehabilitated for sale to low income individuals. As the primary outreach vehicle for the retrofit ramp-up program, this NSP funding facilitated the acquisition of a home for a deep-energy retrofit demonstration. The neighbourhoods of Glen Acres and Vinton are comprised of starter homes built from 1950 – 1970. A significant challenge for market transformation in these communities was the limited ability to communicate directly with homeowners. Because Glen Acres and Vinton are conventional post World War II first ring suburban communities, no community centre or other social meeting place is available for marketing outreach. As a result, no venue existed for the purpose of educating homeowners about the benefits of energy conserving retrofits or available opportunities for grant assistance to implement appropriate retrofits for low income homeowners. As part of the Lafayette program, ultimately named the Lafayette Energy Assistance Program (LEAP), outreach opportunities and potential for homeowner education was provided by a high-profile, deep-energy retrofit demonstration home located within the Vinton community. The use of a deep-energy retrofit demonstration home within the community provided marketing outreach needed to encourage participation by community homeowners. Locating the home within the community helped to make grant implementation convenient for the community within a location appropriate for social interaction, and provided a path for bringing the retrofit program message to individuals who may not be exposed to it in the
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mass media. The demonstration used established energy conservation retrofit strategies as well as alternative energy sources, some of which are beyond the current capability of participating homeowners to adopt, to draw as large an audience as possible. The program exposed homeowners in the target neighbourhoods and the larger Lafayette community to currently available retrofit technologies as well as the available grant incentives. In a December 2010 review of U.S. whole-home retrofit programs, the National Home Performance Council noted that utilities sponsored the majority (113) of the 126 whole-home retrofit programs identified in the study. Of this group, 38 met the home performance guidelines of the Energy Star program sponsored by the U.S. Department of Energy (DOE) and the U.S. Environmental Protection Agency (EPA). To receive a Home Performance designation under the Energy Star program all of the following components must be included in the program. Similar components were used for the LEAP, specifically: • An assessment of the home by a certified energy specialist using visual and diagnostic methods; • A set of recommendations for improving the home based on the assessment; • Assistance for homeowners in identifying contractors who can implement the recommendations; • Verification that work was installed and that health and safety issues were addressed; and • Quality assurance measures. The following narrative presents a synopsis of the Lafayette Energy Assistance Program (LEAP), how it was conceived for funding by the U.S. Department of Energy (DOE), and the basic program implementation. The presentation of case study material introducing the program description and a narrative discussion of steps taken by local program administrators is intended to be instructive for those wishing to develop and implement similar community-scale retrofit programs. This case study is limited to the experiences of the author who has served in the role of technical advisor to the City of Lafayette during the initial funding request period and program administration.
2. Partnership Funding and University Participation As part of the economic stimulus program in 2009 the U.S. government chose energy efficiency as an area where federal funds could be expended to achieve multiple goals. The funds appropriated by the American Recovery and Reinvestment Act of 2009 were primarily intended to stimulate the economy and create jobs. The Energy Efficiency and Conservation Block Grants (EECBG) Program, funded for the first time by the Recovery Act, supported a Presidential priority to promote energy efficiency and the use of renewable energy technologies. Using up to $453.72 million in Recovery Act EECBG funds for a funding opportunity announcement (FOA), the Retrofit Ramp-up Program was initiated. Purdue University saw the Retrofit Ramp-up Program as an opportunity to utilize the skills and resources available in the College of Technology Department of Building Construction Management to assist the limited staff available in the City of Lafayette obtain support from this funding opportunity. The City of Lafayette’s close proximity to campus and recent
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collaboration to seek funding from the State of Indiana for an energy related retrofit demonstration home, which generated interest but was not funded, led to a partnership to develop a Retrofit Ramp-up proposal. Although Lafayette was eligible to receive funding, it was necessary to team with the City of Indianapolis, the nearest major metropolitan area, to generate a funding request large enough to meet the program requirements. The proposal was chosen as one of 25 awards throughout the US in April of 2010. Indianapolis received a grant totalling $10 million of which just over $1 million was allocated to the City of Lafayette. Although no grant funds could be expended beyond April of 2013, delays in final program guidelines from the Department of Energy prevented the agreement between Purdue University and the City of Lafayette from being drafted until late summer of 2010. Purdue University as a subcontractor to the City of Lafayette, a sub-grantee, was relieved from many of the reporting requirements of the program, but retained a substantial requirement to assist the city as the primary advisor to the program. The City of Lafayette community development and redevelopment departments cooperated in choosing a neighbourhood for the retrofit ramp-up that would facilitate community-wide housing retrofit for improved energy performance. Retrofits would be funded through grants to low income homeowners with the deep-energy demonstration of housing retrofit serving as a highly visible example of possible outcomes in a typical neighbourhood home. The Glen Acres and Vinton communities are located in an area with a significant number of foreclosed post World War II homes that are appropriate for energy retrofit. Funds from a U.S. government Neighborhood Stabilization Program (NSP) grant to the City of Lafayette for a comprehensive redevelopment of the same communities was used to provide the necessary city planning staff to complete the project. The NSP funding is intended to finance the acquisition of foreclosed properties that are then rehabilitated for sale to low income individuals. This financing provided the means for Lafayette to purchase a deeply discounted home in foreclosure that would serve as the basis for the deep-energy retrofit demonstration. The two programs utilized had different but compatible goals. The DOE Retrofit Ramp-up Program, later renamed Better Buildings, had the major goal “to stimulate activities that move beyond traditional public awareness campaigns, program maintenance, demonstration projects, and other “one-time” strategies and projects … to stimulate activities and investments which can 1) Fundamentally and permanently transform energy markets in a way that make energy efficiency and renewable energy the options of first choice; and 2) Sustain themselves beyond the grant monies and the grant period by designing a viable strategy for program sustainability into the overall program plan” (Department of Energy, 2009). Others have noted the urgency of energy market transformation that is outlined in the Retrofit Ramp-up funding opportunity because “The full deployment of cost-effective, energy-efficient technologies in buildings alone could eliminate the need to add to U.S. electricity-generation capacity” (National Academy of Sciences, 2010). In contrast, the NSP funding goals sought to stabilize neighbourhoods experiencing significant foreclosure activity through community infrastructure improvements and elimination of vacant housing units. The NSP directly funded housing renovation, or in some
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cases, demolition. Because NSP funds were available to improve both the physical condition as well as the current market viability of the home selected for the deep-energy retrofit, the demonstration home was able to showcase the cosmetic and lifestyle upgrades often chosen by homeowners along with the energy related retrofits being funded under the DOE program. Combining these two grants provided a showcase for a whole-house view of refurbishment services. Whole-house retrofits provide savings in cost and complexity by completing energy conserving measures at the same time that repair or cosmetic upgrades are implemented. A significant example of this was experienced in this case of the deepenergy demonstration home. Air sealing and insulation upgrades were completed with lower cost and complexity because the exterior siding for the home was already being replaced. In parallel with technical research for selection of energy conserving measures (ECM) for the deep-energy retrofit demonstration by faculty and students at Purdue University, a weekly meeting was held with the builder and the NSP program manager. The ECM selection was based on the following guiding principles: • ECMs should be appropriate for most homes in the communities o Easy for local building trades to understand and install o Materials available through traditional supply channels without delay o Performance was assessed from a whole-building viewpoint o With near term potential for positive payback but with no specific cut-off o Priority was given to retrofits that could be funded by program grants o Promote energy conservation first with introduction of alternative energy sources only when energy consumption has been minimized • ECMs obvious to visitors and individuals that passed by the demonstration home were desirable for program visibility and ease of endorsement The combined management of the NSP funding and the DOE funded grants for the Lafayette Energy Assistance Program created a positive synergy. Nevertheless, the local program manager initially involved with the NSP program possessed little knowledge of building technology or energy related construction and at times exercised poor financial management. Delays resulted that prevented the construction activity from progressing at a normal pace. Because of these delays, it was not possible to use the demonstration home as originally intended. A change in the program manager position by the City of Lafayette was made after approximately six months, but the LEAP was well behind schedule. The intended use of the demonstration home was to provide the LEAP marketing outreach. Glen Acres and Vinton are communities with substantially more low-income and minority population than the overall Lafayette population and no venue exists within the communities for the purpose of educating homeowners about the benefits of energy conserving retrofit or available opportunities for assistance in financing and implementing appropriate retrofits for their home. The construction delays prompted the feeling that the demonstration home alone could not be counted on as a source of community outreach. To overcome this possible shortcoming, signage at the building site, frequent public service press and radio releases through Purdue University press outlets, meetings at a community school advertised by neighbourhood signage, and word of mouth from early grant recipients helped to keep the grant program on track.
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3. The Deep-Energy Retrofit Demonstration Home A detailed description of the ECMs chosen for the demonstration home is beyond the scope of this paper. The following list provides basic information about the ECMs. Windows: R-5.56 triple glazed casement Sun Tube: One in each bath with dimmer to provide daylight illumination Exterior Doors: Insulated steel, thermal break frame, magnetic weather-strip, polyurethane core R-8.3 Crawl Space: Damp Proof w/ sealed 20 mil poly floor cover Attic Access: R-40 insulated, weather-stripped attic closure system Air Seal: Air seal all top plates and ceiling penetrations with closed cell foam Expanding foam seal all exterior wall penetrations Insulation: Attic – R-60 Loose Fill Cellulose 3" closed cell foam - 3' at roof edge (R-20+) Crawl Space – 2" closed cell foam on interior of crawl wall and band joist (R-13+) Exterior Walls – R-11 batts @ 2x3 wall cavity plus 4" (R-20) extruded polystyrene sheathing (2 layers of 2” foam with lapped and taped joints) South Overhang: Extend to 16" for summer shading and add continuous vent Hot Water: Heat Pump Water Heater min. COP rating of 2.0 or greater Renewable Energy: Nominal 4 KW Solar PV System Furnace & AC: multi-speed air handler, min. 25,000 BTU gas furnace, 1 ton AC Mastic Seal All Ductwork Energy Recovery Ventilator: min. 60% heat recovery, unit and ductwork installed in conditioned space Thermostat: 7-Day Setback Appliances: Washer Front Load Energy Star Rated Dryer Energy Star Rated Refrigerator Top Freezer Model Energy Star Rated Dishwasher Energy Star Rated Lighting/Electrical: 44 circuit energy monitor, real-time internet energy use dashboard All lighting CFL or T-8 florescent except LED kitchen task lighting Window Coverings: Living Room Insulating Cellular Shades with air sealing tracks Because the deep-energy retrofit home was also a NSP remodel project, the builder chosen to complete the work was a low bidder under the qualification rules of the NSP funding. They had a typical background in residential construction with no special expertise in energy related building. The weekly meetings used in the ECM selection process were an opportunity to provide the builder and some of his subcontractors with the technical requirements of the most unusual of the ECMs. A PhD student made weekly visits to the project site to meet with the builder, the program manager and any subcontractors or material suppliers involved that week. With the builder in charge of day to day work and quality control, occasional performance issues were anticipated.
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While no serious quality control issues were apparent, several things did occur that are indicative of common oversights that can be experienced in energy related retrofit. To verify the energy performance of the demonstration house, an energy auditing firm was hired to complete a post-construction inspection using a blower door and duct blaster to confirm the success in air sealing the structure and ductwork. A preliminary use of the blower door was also utilized before completion of the interior wallboards. At this point the ceiling was complete and all air sealing measures were completed by the builder’s subcontractors. Within a very short period of introducing negative air pressure to the structure, significant flows of cold exterior air were noted entering. Figures 1 and 2 are examples of a few of the many poorly sealed penetrations.
Figure 1: Poor Foam Air Sealing
Figure 2: No Foam Seal at Exterior Penetration
Failure to commission HVAC equipment is common in residential construction. It was no different in the demonstration home. The first time the air conditioning was turned on the air volume from the air handler was so high it caused significant noise within the home and caused papers to blow if located close to an air supply outlet. The multi-speed fan for the system was capable of servicing a range of capacities from 1.5 to 6 tons of cooling. Rather than setting the system for the design parameters, the HVAC installers left the factory preset values in place. In addition to verifying the air infiltration and duct leakage of the completed demonstration home retrofit, the energy auditing firm completed a common U.S. home energy rating called the Home Energy Rating System (HERS). The HERS rating is an index using a score of 100 to represent the performance of homes based on a reference home built to meet the 2006 International Energy Conservation Code. A net-zero energy HERS home score is 0. The lower a home's HERS score, the more energy efficient it is in comparison to the HERS reference home. Figure 3 is the rating certificate with a score of 17 for the deep-energy demonstration home.
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Figure 3: Demonstration Home HERS Rating Certificate While it is not possible to separate all costs related to the energy related retrofits from the major modifications to fully rehabilitate the demonstration home, the final energy retrofit costs were 18% less than original budget for the deep-energy retrofit. Some saving came from carful selection and purchasing of ECMs, but the bulk of the savings resulted from the significant reduction of installed cost for solar PV systems that took place between 2009 when the initial budgeting was completed and the actual installation in 2012. The budget savings allowed three additional grants to be made from program funds for low income homeowners.
4. Program Educational Activities Community outreaches were extensive for the deep-energy retrofit home and retrofit grants. A combination of press coverage, community meetings, open houses, printed handouts, displays, as well as educational seminars for homeowners, contractors and the academic community were utilized. Press coverage began as soon as the funding award was announced, generating interest almost immediately. This was followed by press releases from the City of Lafayette, Purdue University, and the media group in the College of Technology. Press releases were strategically timed to coincide with phases of the project and opportunities for community interaction throughout the grant period. The most significant evidence of community interest came during the open house period in the summer of 2012. The deep-energy retrofit home was staffed by students every weekend. Newspaper and radio advertisement, as well as street signage and word of mouth contact throughout the community supplied a steady attendance. Weekly attendance ranged from 20 to 35, with visitors coming from the entire Lafayette metropolitan area rather than just the targeted neighbourhoods. The consistent attendance prompted the decision to extend the open house period several weeks beyond the original plan.
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To extend the outreach penetration, the demonstration home was included in several activities not directly related to the LEAP. The first was inclusion as part of the International High Performance Building Conference at Purdue University in July of 2012. This conference included a short course on net-zero homes conducted by the author and several others from the College of Technology and a tour of the demonstration home open to all conference attendees. The researchers who attended the tour included individuals with interest in high performance buildings, HVAC performance, and compressor design. Several weeks later the home was included as part of the Parade of Homes conducted each year by the Builders Association of Greater Lafayette. At each of the open houses and special events contact information was collected from individuals interested in more in-depth energy related retrofit education. Over 40% of the visitors provided contact information. This strong response is an indication of the keen interest the visiting homeowners had in learning more about how they can reduce the energy consumption in their homes. To accommodate this interest, a half-day educational seminar was offered for homeowners. Presentations were given on the following topic areas by the author and the PhD student who was involved with supervision of the deep-energy retrofit. • Why save energy? • Energy audit & testing • Specific technologies to reduce home energy consumption • Renewable energy systems for the home • Energy use impact of landscaping, overhangs, site plans • What to watch out for when contracting for a home energy retrofit • Choosing appropriate energy conserving upgrades • Energy Monitoring The handouts and curriculum developed will be used for one additional wintertime open house and homeowner seminar. In the future these materials will serve as a template for anticipated educational outreach for other programs. An additional half-day educational seminar was offered for contractors and suppliers using topics similar to the homeowner seminar. Greater technical depth was offered and the discussion was oriented to the concerns contracting organizations have as they consider business opportunities in energy related retrofit. Attendance at this seminar was built through the contacts that the Purdue University Department of Building Construction Management has developed by working on a number of projects with the Builders Association of Greater Lafayette.
5. Discussion University and student involvement in the project provided benefits to the program outcomes, university community relations, future university research, and student growth. Without the participation of Purdue University, the City of Lafayette would not have initiated a proposal to obtain funds from the DOE retrofit ramp-up. The resulting grants allowed lowincome individuals to reduce monthly costs to help them maintain homeownership in the two foreclosure prone communities. Purdue University received significant notice in the mass media for their participation, emphasizing positive public relations with the City of Lafayette.
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Homeowner education provided detailed information for numerous individuals who did not obtain retrofit grants but were prompted to investigate energy efficient retrofits for their homes. These benefits to the community will continue to accrue for years to come. Two graduate students and six undergraduate students were funded by the program to participate in planning, supervision or community outreach activities. In all cases these students learned a great deal about home energy conservation. In addition, many improved their skills in public interaction. One graduate student is completing his Master of Science thesis on measurements of success in energy use reduction from retrofit work supported by the homeowner grants. Additional research will be conducted on the deep-energy retrofit home performance and on long-term energy use of the homes retrofit through grants. Despite all of the very positive outcomes of the LEAP partnership, not all of the goals of the original retrofit ramp-up concept have been realized. One of the original objectives of the Lafayette program was to reduce the risks that a single construction organization must undertake when they choose to provide energy retrofit services for smaller-scale projects. Most small construction organizations choose not to initiate whole-house energy services activity. They typically lack skills to assess, sell, and complete affordable residential building energy improvements that maximize energy savings for individual homeowners. The need for market transformation based on contractor competency was emphasized in the conclusions of a 2008 report to the State of Vermont reviewing existing programs in the United States that attempt to eliminate first cost barriers for energy efficiency improvements in the residential sector. The report by Merrian Fuller makes six recommendations to the state. The only recommendation not directly related to financing energy related improvements was to expand the network of energy improvement contractors. The report’s author felt that support and action was needed to train more contractors and their crews in a way that will increase the capacity of businesses to serve more customers. They also noted that the programs with the highest volume of energy related loans had a strong contractor network and included regular communication with the contractor network. Within the Lafayette metropolitan area the number of contractors qualified to undertake whole-house energy related retrofits is very limited. In the two years prior to implementing the LEAP, the City of Lafayette had undertaken home renovations which included substantial energy upgrades under the NSP. Only three qualified construction organizations responded to the call for bids even though during this period an economic recession limited participation in other construction activity. The LEAP initially intended to attract small scale residential renovation contractors who would like to expand into energy services contracting. The potential for up to 80 government funded home retrofits in two contiguous communities provided strong market potential. If successful, at the end of the three year program a qualified group of whole-house energy services contractors would be operating in the Lafayette metropolitan area. Subsequent to the final funding document preparation for the Lafayette award, the DOE administrators released guidance about applicability of Davis Bacon wage rules for retrofit activities. Davis Bacon is a series of related acts of the U.S. Congress administered by the
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U.S. Department of Labor (DOL) which require all contractors and subcontractors performing work on federally funded contracts in excess of $2,000 to pay wages and fringe benefits equal or greater than the prevailing wages in the area of the project. In some geographic areas the prevailing rates are established wage rates paid to unionized labour. For small residential projects, the prevailing wage rates may not be heavily influenced by union negotiations. Nevertheless, the current Davis Bacon rules require substantial recordkeeping and reporting. These reporting requirements typically prevent small contractors from participation in federally funded work. As a result, all LEAP retrofit work for homeowners receiving grants were completed under the management of a large general contractor. This conflict of priorities constrained the growth of a viable small contractor base for energy retrofits. Market transformation through growth of a qualified group of whole-house energy services contractors in the Lafayette market did not take place.
6. Conclusion This case study introduces one approach to the world-wide residential energy use challenge presented by the large number of individually owned and operated homes that were constructed when the energy consumed to operate these structures was not a consideration in design and construction. By combining multiple government programs, cosmetic and lifestyle upgrades were completed along with energy efficiency upgrades. This showcase for a whole-house view of refurbishment services where savings in cost and complexity can result from completion of energy conserving measures while completing other housing repairs or cosmetic upgrades is an example for both subsidized and market-rate retrofit. The author’s experiences with this case demonstrate the need for program managers that understands the complexity of energy related retrofit. The case also demonstrated that quality control is a major challenge to successful energy retrofit programs. Over the upcoming years both the demonstration home and the subsidized retrofit homes will be monitored for research to confirm the actual energy reduction benefits of the program. Major benefits accrued to the Glen Acres and Vinton Communities but questions remain about how well the program achieved the originally intended goals. No market transformation took place to increase the supply of contractors pursuing energy services work. Contractor knowledge was improved somewhat, but for the overall city a skills gap persists. In the U.S., natural gas prices are falling, which offers little financial incentive for energy conserving retrofit. Homeowners continue to show a personal preference for visible upgrades. In addition, financing and valuation norms support visible upgrades while at the same time ignoring energy related upgrades. Contractors have no compelling reason to close the skills gap and sell energy related upgrades unless government programs finance the work and promote the energy related investment. In this case conflicting priorities from government wage rate support essentially nullified any incentives for contractors to participate. Thirteen jobs were created by the program in the most recent quarterly report for the DOE grant (Department of Energy 2012), but job creation reporting was not required by small subrecipients of funding such as the City of Lafayette. As a result, it is not clear if any
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Indianapolis or Lafayette jobs were included in the report. Job growth was probably negatively impacted by the Davis Bacon wage rate recordkeeping and reporting requirements as well. These observations serve to demonstrate the potential for failure when competing regulatory interests are not considered in program design. The sharing of additional case study experiences as new energy conserving programs are developed and put into action is encouraged so that others can learn from the experiences and outcomes of each new program. Above all future programs need greater engagement of small contractors typically employed for residential retrofit in program activities. Engaging students in similar programs as part of their normal coursework is also advisable.
References 1. Department of Energy (DOE) (2009) Competitive Solicitation: Retrofit Ramp-up and General Innovation Fund Programs, Funding Opportunity Announcement Number: DEFOA-0000148, Office of Energy Efficiency and Renewable Energy, (available online https://www.fedconnect.net/fedconnect/?doc=DE-FOA-0000148&agency=DOE, accessed on 10/10/2011) 2. Department of Energy (DOE) (2012) Grants – Award Project DE-EE0003577 Summary for April 1 – June 30, 2012, (available online http://www.recovery.gov/Transparency/RecoveryData/Pages/RecipientProjectSummary5 08.aspx?AwardIDSUR=106076&qtr=2012Q2, accessed on 15/10/2012) 3. Department of Labor (DOL) (2011) The Davis-Bacon and Related Acts, (available online http://www.dol.gov/compliance/laws/comp-dbra.htm, accessed on 10/11/2011) 4. Fuller M (2008) Enabling Investments in Energy Efficiency: A study of programs that eliminate first cost barriers for the residential sector, Efficiency Vermont, (available online http://www.greenforall.org/what-we-do/building-a-movement/community-ofpractice/enabling-investments-in-energy-efficiency, accessed on 10/10/2011) 5. National Academy of Sciences (NAS) (2010) Real Prospects for Energy Efficiency in the U.S., (available online http://www.nap.edu/openbook.php?record_id=12621&page=263, accessed on 17/5/2011) 6. National Home Performance Council (2010) Residential Energy Efficiency Retrofit Programs in the U.S.: Financing, audits, and other program characteristics, (available online http://www.nhpci.org/images/NHPC_WHRetrofitReport_201012.pdf, accessed on 10/10/2011) 7. National Science and Technology Council (2008) Federal Research and Development Agenda for Net-Zero Energy, High Performance Buildings, (available online http://www.ostp.gov/cs/nstc/documents_reports, accessed on 10/2/2008) 8. U.S. Green Building Council (2009) Buildings and Climate Change. (available online http://www.usgbc.org/ShowFile.aspx?DocumentID=5033, accessed on 16/3/2009)
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Normative Technical Parameters of Low Energy Buildings
Josifas Parasonis1
Abstract The consumption of fossil fuel is a global problem and the solution of this problem could be the increase of energy efficiency and renewable energy consumption. However, the pace and methods to solve this global problem in general and particularly in construction are insufficient. In different countries, there are energy efficient buildings (passive, environmental, green, smart, sustainable etc.), although generally accepted normative evaluation parameters of energy efficiency of buildings and their impact on the environment are not available yet. The building assessment systems cover a very wide range of parameters. This makes it difficult to assess and analyse the energy efficiency of buildings objectively. The paper proposes to introduce and regulate the coefficient of energy stock ratio, which will promote the use of renewable resources. Motion made searching for technical regulatory parameters to describe low energy buildings. According to the analysis of global energy situation, experimental buildings designing and calculations are proposed with normative values of the parameters (energy stock ratio - er, final annual energy consumption - Qa) for low energy buildings at the use stage. The principal of the proposed methodology (energy stock ratio coefficient) is suitable not only for the construction, but for every technological process to assess the use of energy resources regarding the consumption of efficient and renewable energy and environmental impact.
Keywords: stock energy ratio, low energy building, regulation, normative parameter, environment
1. Introduction Our society has come into such a stage, when consumption of fossil fuel has become a 1
Head, professor, Architectural Engineering; Vilnius Gediminas Technical University, Saulėtekio al. 11, LT01132 Vilnius, Lithuania;
[email protected];
[email protected]
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global problem. The solution of this problem could be the increase of total possible effective consumption of energy resources, search for new ones, increase of the consumption of already known renewable energy resources. The society cannot exist to unlimited extent using finite energy resources. Since buildings represent about 40% of all energy use and they are the largest source of emissions in Europe, the EU has addressed the problem by introducing minimum requirements for the energy performance of buildings. In 2002 the EU adopted Directive 2002/91/EC of the European Parliament and of the Council dated 16 December 2002 on the energy performance of buildings, which committed the Member States to apply minimum requirements regarding the energy performance of new and existing buildings, ensure the certification of their energy performance and require regular inspection of boilers and air conditioning systems in buildings. By its Second Strategic Energy Review the European Parliament approved on the Council of 19 May 2010 the EU new Directive 2010/31/EU on the energy performance of buildings (recast)[1]. In order to protect environment from the surplus of emissions and saving energy resources clean, green, energy efficient, passive, zero energy sustainable buildings are being used increasingly. Usually, the definitions of these buildings are similar, still their characteristic parameters are quite different, and for example, eco or green buildings may not necessarily be energy-efficient. Apparently, one of the reasons for this situation is that building assessment systems cover a very wide range of parameters. Two of these certification systems are widely used in the world. One of them is American, called LEED (leadership in energy and environmental design)[2]. It is the most common so that it already has more than 5000 internationally certified projects. It was founded in 1998 and based on the U.S. Green Building Council. LEED is the only system, which is used in South America and in Africa, Europe and Asia. The oldest and most extensive in Europe is the British system BREEAM [3]. It is the second system that functions internationally in North America, Africa, Europe and Australia. All other systems until 2009 are only working at national level: DGNB (German)[4], HQE (French)[5], CASBEE (Japan)[6], Green Star9 (Australia)[7] and other. These certification systems are analysed in the Longlife*) project reports [8, 9]. Today the situation is such that all types of buildings in generally have not approved definitions [8-10]. Also there are no low energy buildings in Europe with standardized parameters. In connection with the new Directive 2010/31/EU increased emphasis in the last period on the Zero Energy Buildings [10-16]. The Zero Energy Building definition in the Directive includes the use stage. Regulations of energy efficient building for energy demands in various countries differ a lot. In this research the proposed technical parameters of the energy efficient buildings, which would help to standardize the identification of low energy buildings, are described.
2. Global situation of overall consumption of energy resources The structure of energy production and consumption necessitates transformation. There are lots of scenarios of consumption development, where decrease of fossil fuel (nonrenewable) consumption and increase of renewable energy sources are mentioned. Fig. 1 presented by Shell and International Agency of Energy (IAE) [17] shows energy production development of different fuel sources in overall fuel balance.
14
Figure 1. Development Energy production of different fuel sources According to chart lines shown in Fig. 1, there was decrease of carbon consumption in the beginning of the 20th c., when oil and gas were discovered. In 1980s there was decrease of oil extraction and in short time the decrease of gas extraction is expected. That is why increase of renewable energy resources development is expected and in overall it will make up to 30 % of all global fuel in 2050. In this respect there are more optimistic scenarios [18]. Fig. 2 shows highly aspirated, but more realistic, the so called- AIP (Advanced International Policy) scenario. ______ *)The Longlife project is carried out under the Baltic Sea Region 2007-2013 programme: “Sustainable, energy efficient and resource saving, residential buildings in consideration of unified procedures and new and adopted technologies”.
Figure 2. Global energy production scenario by EREC (European Renewable Energy Council)
Fig. 2 (1 – geothermal; 2 – solar heat; 3 - solar electricity; 4 – wind power; 5 – small HE; 6 – large HE; 7 – biomass power) reveals that it can be achieved in 2040, that 50% of all served energy could be renewable energy. On the other hand, global experience of fossil fuel consumption reveals its very low effectiveness. There is estimation [19], that primary energy (the energy of renewable and non-renewable energy resources that was not converted or transported in any way) in overall is consumed only in 30% (Fig. 3).
15
Figure 3. Energy consumption efficiency of non-renewable energy resources. Considering the above mentioned, not only in the construction industry, but the use of energy resources in technological processes in general state of the world can be described as follows: • Effectiveness of energy consumption must be increased in all possible ways; • Energy production should be transformed with increase of renewable energy resources consumption.
3. Standardization of energy effectiveness in building construction industry technological processes Sustainable development [8, 9, 20,21] plans environmental protection, every possible pollution reduction, and efficient use of natural resources. Over the past decade European Parliament and the Council, adopted a number of important resolutions and directives on energy efficiency. All of this is important in case of building construction industry. As for intentions of the construction industry as a whole, this would mean that its energetic efficiency of the renewable and non-renewable energy resources should be compared throughout its product life cycle [8, 9, 16, 21, 22]: • raw materials production; • production of elements, structures; • transportation of materials, elements, structures; • technological process of construction period; • building use period (heating, air conditioning, hot water production, other domestic needs); • building demolition; recycling of its materials, elements, structures. A change of energetic resources in favour of renewable energy resources makes better ecological parameters and better impact on environment. To promote this change, the new energy efficiency parameter of technological processes to be introduced is proposed: energy stock ratio er (the ratio of fossil fuel (non-renewable) and renewable sources of energy, necessary for a technological process). Apparently, it would be helpful not only in construction industry, but in general for all, and especially in the technology industry, pursuing sustainable development and significant environment protection results. Considering all this, low energy building during its life cycle could be defined by two technical parameters of energy [9]: • normative annually final energy consumption (kWh/m2a);
16
•
coefficient er (energy stock ratio) of energy consumption (ratio of fossil fuel and renewable energy resources needed for normative functioning of building). If the energy stock ratio er value for energy efficient building, for example, could be equal to 2, renewable sources will supply the building in one-third of the total energy demand. It is clear that the regulatory energy factor value must be based on the special research for each technological process and technical possibilities. Of the above, to describe the needed energy efficiency of the building life cycle, not only of the building use period we have to identify and normalize the energy stock ratio er regulatory values for total building life cycle [9]. Today we have the biggest amount of the needed data to find out at least the energy stock ratio er value on the period of the building use.
4. The overall annual energy demand of low energy building It should be decided of the amount of normative annual energy consumption, after analysis of normative regulations of different countries and experimental designs of low energy building are done [8, 23, 24]. Analysis of normative regulations of European countries reveals that, there are only 7 countries where there are normative regulations of low energy buildings: Austria, Czech Republic, Denmark, Finland, France, Germany and United Kingdom. Normative regulations of these countries are shown in Table 1. Table 1. Normative annual energy consumption regulations of low energy buildings Country
Austria Czech Republic Denmark
Normative annual energy consumption 2 kWh/m a (heating, air conditioning, hot water production, other domestic devices) 60 - 40 51 - 97 35
Finland France
40 -45
Germany United Kingdom
40 - 60 Planned value from 2013- close to passive building value
Notes
Bigger value is in private residential sector C class Without consumption for lightening and domestic devices. Project of normative regulation At the moment energy consumption is normalized Depending on climate (location). With lightening needs, without needs for domestic devices. At the moment building regulations are not compulsory
It should be mentioned, that European Community has common methodology of evaluating [25], and still there are difficulties of result comparison, because of national specificity. The reasons of differences are: • internal or external measures evaluating heated area; • variations of inner heat additions; • differences in parameters of comfort conditions; • inclusion of unheated areas in the calculations; • differences of climate conditions. Influence of climate conditions based on passive building built in Lithuania is shown in Table
17
2 [26]. Table 2. Energy consumption for heating of passive building in different climate conditions Country Germany Austria Switzerland Denmark Ireland Poland Finland Lithuania
City Hanover Salzburg Bern Copenhagen Dublin Warsaw Helsinki Vilnius
2
Yearly energy consumption for heating, kWh/m a 11.2 7.4 8.4 10.4 3.9 14.5 24.3 15
Passive one household residential house, in Vilnius (Lithuania) climate conditions, was designed evaluating that annual energy consumption for heating is 15 kWh/m2. Other data: building gross area- 194.9 m2, heat transfer coefficient – walls- 0.1 W/m2 K, roof – 0,07 W/m2 K; windows –from 0.73 to 0.83 W/m2K; annual energy consumption – 107 kWh/m2; tightness, if there is 50 Pa pressure difference, – 0.4 h-1. Table 2 data reveals that climate conditions influence is big and differences in energy consumption for heating are radical: varieties from 3.9 to 24.3 kWh/m2 per year. It means that, if energy consumption of low energy buildings will be regulated, in different European countries these buildings will be designed using different thermodynamically parameters or different engineering solutions will be used to compensate the heat loss difference because of climate conditions. Evaluation of low energy residential building made by Lithuanian partners of Longlife project [9, 10] is based on pilot design proposal. Building has 4 floors, two staircases, oriented by diametrically opposite angles in North- South direction. There are in total 26 flats: 8 flats have 1 room (38,1m2); 10 flats have 2 rooms (57,3 m2); 4 flats have 3 rooms (82,6 m2); 4 flats have 4 rooms (111,1m2). External dimensions of the building 33.2*16.2*14 m. Total heated area- 1980 m2, area of the windows on different sides of the building: SE - 320 m2, NW – 160 m2, NE – 0, SW – 50 m2. Heat conduction coefficient of external surfaces: Uwall = 0,20 W/m2K, Uroof =0,15 W/m2K, Uwindow= 1,3 W/m2K, Ufloov = 0,25 W/m2K. All flats are equipped with individual heat recovery air handling units, mechanical ventilation air change rate Nmech = 0,5 h-1, infiltration air change rate ninf =0,2 h-1. Internal height of the flat is 2.9 m. Amount of building occupants is 58 persons. Area of solar collector for water heating is 85 m2. Energy consumption data of the building is shown in Table 3. Heat demand is calculated in accordance with Lithuanian Building Technical Regulations (STR 2.09.04:2008 Power of heating system; STR 2.02.09:2005 Heating, ventilation and air conditioning). The Regulations are based on EN 12831:2003, EN 832:1998/AC:2002 and EN ISO 13790:2004, EN ISO 13370:2007. Results shown in the Table 3 do not include energy consumed by internal lightening and domestic devices. This result correlates well with regulatory values of the low energy building in European countries shown in Table 1 and is close to the aspirations of the Longlife project [9]. It seems, that the two suggested normative regulatory values for the design of low energy buildings must be enough, as far as of the building use phase. Longlife project partners agreed with this proposal [9]. Socio cultural, functional and other technical parameters are already assured now through Basic building requirements: stability, longevity, safety, hygienic, acoustics, and impact on environment, fire protection. If we mast
18
Table 3. Energy consumption data of the low energy residential building (Longlife LT partners pilot project) 2
Parameters
Annual energy consumption, kwh/m a
Thermal demand for heating (heat pump COP 4,00) and ventilation (heat recovery 80%) Thermal demand for hot water
77,16
36,39
22,61 Solar gains 4,67 Internal gains Electricity energy demand (pumps, 12,6 recuperates, elevators) Energy produced by solar collectors and 16,71 4x3kW vertical axis wind turbines Finally energy demand 31, 44
to certificate a low energy building, the most important parameters are the energy requirements. For energy saving over the building life cycle it would be valuable to find relations between the two suggested parameters at all stages. The result of such our attempt is shown in Figure 4, which depicts a hypothetical link between these parameters of the building use phase.
Figure 4. Hypothetic curve representing energy stock ratio er and annual finally energy consumption of residential buildings Qa Year 2010 reflect the current average situation of European Union countries in the residential sector [8]. For the proposed energy efficient building design in 2015 the regulatory factor for energy stock ratio er = 2 and the overall annual energy demand 40-50 kWh/m2 a value is suggested. Fig. 4 reveals that there is a field (Fig. 4., drawn in lines) where in the intersection of the two parameters the building falls into the category of low energy. Extension of the curve after the year 2015 in the growth direction of annual energy consumption is disputable. It is clear, that effective consumption of energy resources will be topical issue, though total energy saving in the context of increasing renewable energy resources consumption will not be so important. On the other hand societal development reveals in the further the bigger energy consumption. That is why hypothetical draft lines of suggested parameters shown in Fig. 4 are yet to be researched.
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5. Conclusions Energy situation in the world forces to increase consumption of renewable energy resources. To assess this, normative er (energy stock ratio) coefficient value of fossil fuel (nonrenewable) and renewable energy resources ratio should be used and normative regulations of this coefficient should be made for the stimulation of the use in technology processes renewable energy resources. The energy stock ratio coefficient is appropriate to use not only in the construction sector. It is appropriate to normalize the er for all industrial technological processes. This would significantly improve the ecological situation in the world. Life cycle energy efficiency of the building should be valued by er coefficient value of fossil fuel and renewable energy stock ratio (taking into account periods of raw materials, elements and structures production, construction, operational (use) period, demolition and recycling). For the design of low energy buildings, normative er coefficient value of fossil fuel and renewable (energy stock) ratio should be used and normative regulations of this coefficient should be made. Requirements of the Directive 2010/31/EU, that in 2020 the buildings could be nearly zero energy, requires to this period to achieve the energy stock ratio value er < 1. The normative value of 40-50 kWh/m2 of the gross area for the annual final energy demand (for the building use period) mast be no later than in 2015.
References 1. The Directive 2010/31/EU of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings, Official journal of the European Union, 53, 2010. 2. LEED (Leadership in energy and environmental design), for homes rating system. U.S., Green Building Council, January 2009, 114 p. 3. BREEAM – BRE environmental & sustainability standard: BES 5064: issue 1.0. BREEAM Multi-residential 2008 assessor manual. BRE Global 2008. 4. German Sustainable Building Certificate. Structure –Application – Criteria. German Sustainable Building Council. DGNB, 2009. 47p. 5. HQE 12-2009: http://www.assohqe.org. 6. CASBEE 12-2009: http://www.ibec.or.jp/CASBEE/english/index.htm. 7. Green Star 12-2009: http://www.gbca.org.au/green-star. 8 Longlife 1 (2010): Analysis and comparison, Report on the analysis of state of technology, administration and legal procedures, financial situation, demographic needs, similarities and differences in the participating countries, Denmark, Germany, Lithuania, Poland and Russia. Edited by Klaus Rueckert, Josifas Parasonis and other project partners, TU Berlin publication, 492p.
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9. Longlife 2 (2010): Development of standards, criteria, specifications, Report on sustainable buildings, engineering and technology standards, administrative, legal and tendering procedures, economic and financial models, assessment of sustainability, life cycle and operating costs. Edited by Klaus Rueckert, Josifas Parasonis and other project partners, TU Berlin publication, 346p. 10. P. Torcellini, D. Crawley (2006) “Understanding zero-energy buildings”, ASHRAE Journal 48 (9) 62-69. 11. P. Torcellini, S. Pless, M. Deru, D. Crawley (2006) Zero Energy Buildings: A Critical Look at the Definition, in: ACEEE Summer Stud, Pacific Grove, California, USA. 12. A. Marszal, P. Heiselberg, J. Bourrelle, E. Mussal, K. Voss, I. Sartori, A. Napolitano (2011), Zero Energy Building – A review of definitions and calculation methodologies nergy and Buildings 43: 971-979. 13. M. Noguchi, A. Athienitis, V. Delisle, J. Ayoub, B. Berneche (2008) Net Zero Energy Homes of the Future: A Case Study of the EcoTerraTM House in Canada, in: Renewable Energy Congress, Glasgow, Scotland, July. 14. M. Heinze, K. Voss (2009) Goal zero energy building – exemplary experience based on the solar estate Solarsiedlung Freiburg am Schlierberg, Germany, Journal of Green Building 4 (4). 15. D. Crawley, S. Pless, P. Torcellini (2009) Getting to net zero, ASHRAE Journal 51 (9):18-25. 16. P. Hernandez, P. Kenny (2010) From net energy to zero energy buildings: defining life cycle zero energy buildings (LC-ZEB) Energy and Buildings 42 (6): 815-821. 17. Shell energy scenarios to 2050, 2008, 52p. 18. EREC-Europian Renevable Energy Council, 2009. 19. Hegger, M., et al (2008) Energy Manual: Sustainable Architecture. Birkhauser, Basel, Boston, Berlin. Edition Detail, Munich, 280 p. 20. Earth Summit. Agenda 21. The United Nation Programme of Action from RIO, 1992. 21. ISO 15392:2008(E) Sustainability in building construction – General principles, 20 p. 22. A. Dodoo, L. Gustavsson, R. Sathre (2011) Building energy-efficiency standards in a life cycle primary energy perspective, Energy and Buildings 43:1589-1597. 23. J.Parasonis, A. Keizikas (2010) Possibilities to reduce the energy demand for multistory residential buildings, The 10th International conference “Modern building materials, structures
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and techniques”, May 19-21, 2010, Vilnius Gediminas technical university, Selected papers, 989-993. 24. J.Parasonis, E.Juodis, A.Keizikas (2011): Energy efficient building design legal basis, 8th International Conference “Environmental Engineering”, May 19-20, 2001, Vilnius, Lithuania: selected papers. Vol. 2. Water Enguneering. Energy for Building. Vilnius: Technika, p.794798. 25. ErP Directive 2009/125/EC, OL L 285, 2009 10 31, p. 10. 26. N. Venckus, R. Bliudzius, A. Endriukaityte, J. Parasonis (2010): Research of low energy house design and construction opportunities in Lithuania, Technological and Economic Development of Economy, 16(3): 541-554.
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Cost Effective Energy Savings in Australian Commercial Buildings to 2020 Phil Harrington1, Trevor Lee2, David Devenish3, Phil McLeod4
Abstract This paper analyses the level of cost-effective energy savings that new commercial buildings could achieve in Australia by 2015 and 2020, relative to buildings compliant to the Building Code of Australia (BCA2010). It draws on research undertaken by the authors for the Australian Government (Department of Climate Change & Energy Efficiency). The study involved modelling typical a healthcare/hospital building form, a supermarket form, and 3storey and 10-storey office building forms in all capital city climate zones in Australia, at a range of energy performance levels down to zero net energy (where achievable). The results show that there are very significant cost effective opportunities for energy savings in new commercial buildings in Australia even by 2015, and greater opportunities by 2020. While there are variations in the degree of cost effective savings by climate zone and by building type, these variations are around mean values which are high and quite robust in the face of the sensitivity analyses included in the study. Savings of between 54% and 80% are shown to be cost effective for commercial buildings in the Base Case (i.e. on current policy settings), with an average value of 68% by 2020. This high level of cost effective savings is attributed primarily to the relatively low stringency for commercial buildings in BCA2010, which means that many opportunities for energy savings that were cost effective at that time were not taken up. Energy prices for electricity and gas, and also the mix of fuels used in different building types and climate zones, influence the results. With rising energy and carbon prices through time, more such opportunities also become cost effective by 2020. Keywords: commercial buildings, energy savings, cost effectiveness
1. Background The study from which the results are drawn is a contribution to the National Building Energy Standard-Setting, Assessment and Rating Framework measure described in the National Strategy on Energy Efficiency (NSEE), approved by the Council of Australian Governments (COAG) in July 2009 (COAG 2009). The COAG Framework aims inter alia to lay out a pathway for future stringency increases in the Building Code of Australia (BCA) to 2020, in
1
Principal Consultant, Pitt&Sherry, GPO Box 94, Hobart TAS 7000 Director, Energy Partners, PO Box 1211, Fyshwick ACT 2609 3 Senior Mechanical Engineer, Engineering Solutions Tasmania, 199 Macquarie St, Hobart TAS 7000 4 Consultant, Pitt&Sherry, GPO Box 94, Hobart TAS 7000 2
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order to increase certainty for stakeholders and to facilitate strategic planning and innovation by industry. The study commenced in the first half of 2011, and initial assumptions on gas electricity prices were revised to take into account the carbon price. It should also be noted that assumptions on photovoltaic costs are in hindsight conservative, with costs having fallen more dramatically than assumed in the modelling.
2. Methodology This section outlines the approach used to undertake the study.
2.1 Building types Four commercial building types form part of the study; a 3-storey and 10-storey office building, a supermarket, and a health-care building. 2.1.1 3-storey and 10-storey office building details Table 1 below shows the details of the 3-storey and 10-storey office buildings. The Base Case assumes minimal compliance with BCA 2010 using conventional technologies, such as variable air volume (VAV) HVAC plant with economy cycle and hot water terminal reheat, and air cooled chiller and gas-fired boiler with 80% efficiency. Table 1: 3-storey and 10-storey office form 10-Storey Office
3-Storey Office
2
10,000 m
NLA
9,000 m , (10% common areas)
Ratio of length to width
1:1
1:2
Storeys
10 storeys of 3.6m overall height each
3 storeys of 3.6m overall height each
2
2,000 m
2
Area Total (GFA)
services
and
2
1,800 m , (10 % services and common areas)
Floor Plan
Carpeted, open plan within zones
Replication
All floors identical
Occupancy
1 person per 10 m of NLA
Ventilation
7.5 l/s per person
2
Internal loads
15 W/m2
Electric hot water Lighting Air changes Lifts
4 litre/person/day 2
2
Offices- 9 W/m Services & Common areas - 5 W/m Allowance of 1.5 l/s.m2 for the perimeter zone Annual energy consumption 24 MWhr.
Source: Engineering Solutions Tasmania and Energy Partners
Table 2 below shows the HVAC details for the 3 and 10-storey offices.
24
Table 2: Office building HVAC details 10-Storey Office
3-Storey Office
Zoning
4 perimeter zones, 1 interior zone. Central core unconditioned. Note the zoning visible in the figure above. The perimeter zones are 3.6m deep.
Plant type
Central plant, VAV with economy cycle and hot water terminal reheat
Boilers
Gas-fired with 80% efficiency
AHUs
Single AHUs for each zone, i.e. 5 AHUs serving whole building
Control Strategy
14 C supply air temp which is reset in the perimeter zones based on room temperature.
o
Source: Engineering Solutions Tasmania and Energy Partners
Table 3 below shows the glazing details of the office buildings. Table 3: Office building glazing details Location
U-Value
SHGC
Window to Wall Ratio
Fenestration height
External
Internal
Climate Zone 1
4.7
0.44
0.9m
25%
31%
Climate Zone 2 & 5
4.7
0.44
1.2m
33%
41%
Climate Zone 6
3.4
0.38
0.9m
25%
31%
Climate Zone 7
3.4
0.41
0.9m
25%
31%
Source: Engineering Solutions Tasmania and Energy Partners
2.1.2 Healthcare Building The Healthcare model is similar to the 10-storey office building but reflects the greater importance of external views for patient care and has a 2:1 length to width ratio compared with 1:1 for the office building. The healthcare simulation is based on guidance provided by the BCA under the simulation protocol for a Class 9a Ward and that of actual experience with a healthcare facility as provided by Partridge et al (2008). Table 4 below summarises the Healthcare building details. Table 4: Healthcare building details Storeys
10
Ratio of length to width 2:1 NLA Occupancy
9,000m
2
Ward: 1 person per 10 m
2
Treatment: 1 person per 5 m Hot Water
2
70 litres/patient.day 430 patients total Gas-fired boiler (80% efficiency)
Internal Loads
Ward: 5 W/ m
2
25
2
Treatment: 15 W/m 2
Lighting
Ward: 10 W/m (Continuous) 2
Treatment: 7 W/m (JV3 Profile) Plant Operation
24/7
Lifts
147 MW/hr annual energy consumption
2.1.3 Supermarket The Supermarket model is a typical suburban, standalone, single-storey supermarket. The external walls are steel clad, insulated with glass fibre quilting and building foil, and lined internally with plasterboard. The building is all-electric with space cooling dominating energy use. A ducted direct expansion heat pump system (Constant Air Volume (CAV) HVAC) is used in the BCA2010 solution. Space heating is limited to cooler climate zones, where it makes up a small portion of total energy use. The building dimensions, insulation details and window areas of the BCA 2010 supermarket are shown below in Tables 5, 6, and 7, respectively. Table 5: Supermarket building dimensions External Wall Dimensions (m)
Internal Floor Dimensions (m)
Width
79.8
79.3
Depth
53.4
52.9
Ceiling Height
4.2
Source: Energy Partners
Table 6: Supermarket insulation details Climate Zone
Insulation Type
Total 2 (m K/W)
R-Value
Total 2 (W/m K)
1 and 2
Medium Weight Glass Wool (high performance panels)
3.37
0.297
5, 6 and 7
With EPS Expanded Polystyrene (Standard)
2.808
0.356
U-Value
Table 7: Window area (front of building) to meet DTS when facing north Climate Zone Height of Window (m) Total Width of Window (m) 2
Window Area (m )
1
2
5
6
7
2.12
2.12
2.25
2.23
2.06
53
53
53
53
53
112.36
112.36
119.25
118.19
109.18
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2.2 Energy saving improvements Starting with a BCA 2010 minimally compliant design using standard technology, the energy consumption baseline of each building type was established. Then, using the thermal analysis package, ‘Virtual Environment’ Version 6.2, the Base Case buildings were modelled with various improvements in order to meet increasingly higher energy performance levels: BCA2010 –40%, BCA2010 –70% and BCA2010 –100% (or zero net energy buildings). Modelling was undertaken in each state/territory capital city climate zone of Australia. Table 8 below summarises the key variations modelled5, for both office buildings and the health building, to achieve the required performance levels. Table 8: Energy savings improvement to Health building and Offices Health Building and Offices 40% energy reduction •
Increased insulation levels (including lower U-value glazing)
•
Improved HVAC
•
Reduced infiltration to perimeter zone of building
•
Condensing boilers for HW
•
Regenerative braking in 6 lifts
•
Lighting improvements 2 (lower W/m )
70% energy reduction •
Further lighting improvements
•
Advanced glazing
•
Co-generation in 10-storey office (cold climates only),
•
Trigeneration (health building)
•
Preheating hot-water (through PV or cogen)
•
Roof-top photovoltaics
100% energy reduction • • • •
Reclaim ventilation ‘Switchable’ glazing Trigeneration (10-storey office) Maximum utilisation of PV
Table 9: Energy savings improvement to Health building and Offices Supermarket 40% energy reduction
70% energy reduction
Same as 3 storey office, expect:
Same as offices except;
• • • •
Greater improvements in lighting Improved insulation to cold and freezer rooms More efficient refrigeration cabinets CAV HVAC
• •
Further lighting improvements More efficient CAV
100% energy reduction • • • •
Solar HW Refrigeration Cabinets to HEPS with selective heat sink to ambient Advanced fenestration SHGC to suit climate Maximum utilisation of PV
5
Comprehensive details of energy saving improvements, and savings that individual improvements provide, can be found in the report at http://www.climatechange.gov.au/publications/nbf/pathway2020-increased-stringency-inbuilding-standards.aspx 6
Note that regenerative drive systems reduce Base Case lift energy consumption down to 17.6 MWhr and 107.8
MWhr for the office and health buildings respectively. They are considered in all the reduced energy scenarios.
27
The implementation of Cogen/Trigeneration systems affected the design strategy of the building, in that the availability of ‘waste’ heat from these systems means that the building needs to be designed to minimize the cooling requirements rather than heating requirements. As a result improving the energy performance of the building involved balancing the availability of waste heat and the U-values of windows. Furthermore, it was found that there was noticeable difference in the glazing requirements of the Health building (24 hour operation) and the Offices. For the office buildings in warmer climates, the same reductions in U value as the Health building could not be justified since they generally benefit from being able to passively release heat through windows at night.
2.3 Cost estimation A quantity surveyor, Davis Langdon, provided cost estimates associated with achieving the different energy performance levels for each building type and climate zone studied, based on the building specifications detailed above. Regional variations in the costs of plant and materials, as well as climate zone based variations in the building specifications, were taken into account. The analysis provided a commercially-relevant incremental cost to be established for improving each building type to the required 40%, 70% and 100% energy savings relative to BCA2010. The incremental or additional costs of each scenario relative to the BCA2010 Base Case were then calculated as an input into the benefit cost analysis.
2.4 Benefit Cost Analysis The benefit cost analysis considered the value of (purchased) energy savings over an assumed 40 year building life arising from the higher energy performance requirements modelled, compared to the energy costs that would have been incurred had the same buildings been constructed to BCA2010. This means, for instance, that energy derived from a building’s PV installation is represented as a reduced requirement for purchased electricity7. Separate calculations were made for each scenario, building type, climate zone and performance level from 2015 (the first year in which savings are assumed, due to application of higher building energy performance standards) through to 2060. Electricity prices were constructed as the sum of major cost components, comprising wholesale costs, network (transmission and distribution) cost, operating costs, and retail margin. Real network costs were assumed to increase by 1% per year to 2020, and remain constant thereafter. Retail operating costs, derived from the cost component data, are assumed to remain constant in real terms throughout the projection period. The wholesale cost component was calculated as the sum of two sub-components. The lesser subcomponent is costs other than the direct cost of purchased electricity and the major subcomponent is the average pool price of sent out cost of electricity generated. The approach used to construct projected natural gas prices was similar to that used for electricity. For this
7
Note that this values the output of PV systems at the prevailing retail price – other assumptions could be made, but we note that different arrangements for the pricing of PV apply in each state.
28
analysis, energy prices reflect the decisions announced in the Government’s Clean Energy Package (2011) and underpinning Treasury modelling, including a carbon price of $23/t in 2012 rising at 2.5% (in real terms) per year for two years and then assumed to increase 4% per year. Learning rates were modelled by assuming reductions in the real costs of building materials used to reduce future energy costs for the Base Case (15% by 2015, 30% by 2020). The cost reduction is meant to encompass reduced labour costs resulting from learning, lower manufacturing costs from scale economies and market competition, and new technology developments that offer equivalent outcomes at lower costs. The benefit cost analysis used a real discount rate of 7% in accordance with The Office of Best Practice Regulation for present value calculations.
3. Results Table 10 below shows the BCRs that are attained by the 10 storey office. By 2020, it is cost effective at BCA2010 -40% in all climate zones except Hobart and Canberra. Even at the BCA2010 -70% level, it remains cost effective in Brisbane and Darwin. Higher electricity costs in Brisbane, and the high cooling load in Darwin, help explain this result. Table: 10 Storey Office - Benefit Cost Ratios of Energy Savings by Capital city, Year 40%
100%
70%
2015
2020
2015
2020
2015
2020
Sydney
1.0
1.2
0.6
0.7
0.1
0.2
Darwin
1.6
1.9
0.9
1.1
0.2
0.3
Brisbane
1.3
1.6
0.8
1.0
0.2
0.2
Adelaide
1.1
1.3
0.7
0.9
0.2
0.2
Hobart
0.7
0.9
0.5
0.6
0.1
0.1
Melbourne
0.8
1.0
0.6
0.7
0.1
0.1
Perth
1.1
1.4
0.7
0.9
0.2
0.2
Canberra
0.7
0.8
0.4
0.4
0.1
0.1
Average
1.0
1.3
0.6
0.8
0.1
0.2
3.1 3-Storey Office Table 11 below shows the BCRs that are attained by the 3 storey office. The 3 storey office responds better than the 10 storey office. It is cost-effective in all climate zones at BCA40%, and preserves this cost-effectiveness at BCA2010 -70%. In percentage terms, the incremental construction costs required to reach these energy performance levels are quite modest, of around 7% and 11% respectively. This may be explained by the absence of trigeneration systems in this building. Incremental costs and benefits remain reasonably proportionate until at least the 70% energy reduction level, leaving BCRs relatively unchanged. At the -100% level, however, incremental costs jump up to around 46% above the Base Case, rendering this step not cost effective in all climate zones
29
Table 11: 3-Storey Office: Benefit Cost Ratios of Energy Savings by Capital city, Year 40%
70%
100%
2015
2020
2015
2020
2015
2020
Sydney
1.3
1.6
1.3
1.6
0.4
0.5
Darwin
1.2
1.5
1.4
1.6
0.4
0.5
Brisbane
1.4
1.6
1.4
1.7
0.5
0.6
Adelaide
1.6
1.9
1.7
2.0
0.5
0.6
Hobart
1.5
1.8
1.4
1.8
0.4
0.5
Melbourne
1.2
1.5
1.3
1.6
0.4
0.5
Perth
1.4
1.8
1.5
1.8
0.5
0.6
Canberra
1.2
1.5
1.1
1.4
0.3
0.4
Average
1.4
1.7
1.4
1.7
0.4
0.5
3.2 Supermarket Table 12 below shows the BCRs that are attained by the supermarket. The supermarket reaches very attractive benefit cost ratios. In Darwin and Brisbane, for example, the present value of energy savings at BCA2010 -40% in 2020 exceeds that of cost by around 6 times. Even in Canberra, which has the lowest cost effectiveness for this building type, the BCR is greater than 3 at this performance level. At BCA2010 -70%, the supermarket remains costeffective in all climates. Even at BCA2010 -100% - that is, zero net energy – the supermarket is cost effective in 2020 on average across Australia registering BCRs of at least 1 in all climates except Hobart and Canberra. The primary explanation of the high cost effectiveness of energy savings for the supermarket is its relatively simple form, including low glazing ratio and single storey, expansive form – together with the modest performance requirements implicit in the BCA2010 starting point. Relatively straightforward treatments to HVAC systems and lighting, and improvements in refrigeration cabinets to currently projected ‘high efficiency performance standard’ or HEPS, and additional insulation of cool and freezer rooms, significantly reduce energy consumption. The building’s mechanical services are able to ‘free ride’ on the reduced heat output modelled from improved refrigeration and lighting systems. Ideally additional sensitivity analysis would be conducted to test the importance of this factor. Table 12: Supermarket - Benefit Cost Ratios of Energy Savings by Capital city, Year 40%
100%
70%
2015
2020
2015
2020
2015
2020
Sydney
3.9
4.7
1.5
1.8
0.9
1.0
Darwin
4.8
5.9
2.2
2.6
0.9
1.0
Brisbane
5.0
6.0
1.7
2.1
1.0
1.2
Adelaide
4.5
5.4
1.7
2.1
1.0
1.2
Hobart
3.0
3.6
1.3
1.6
0.7
0.9
30
Melbourne
3.2
3.9
1.3
1.6
0.8
1.0
Perth
4.4
5.4
1.7
2.1
1.0
1.2
Canberra
2.7
3.3
1.1
1.4
0.6
0.8
Average
3.9
4.8
1.6
1.9
0.9
1.1
3.3 Health building Table 13 below shows the BCRs that are attained by the healthcare facility. The healthcare facility performs well at BCA2010 -40%, being cost effective in all climate zones. As noted earlier, the health facility is unable to reach BCA2010 -70% without purchasing Green Power to supplement on-site renewable energy generation, with the sole exception of in Darwin. Gas savings, relative to the Base Case, are negative – as the buildings are using trigeneration to cover as much electrical load as possible but at the expense of additional gas consumption – with the net result that realised purchased energy savings are much less than 70%, indeed only around 10% to 20%, and even negative in Darwin. Table 13: Health Building - Benefit Cost Ratios of Energy Savings by Capital city, Year 40%
100%
70%
2015
2020
2015
2020
2015
2020
Sydney
1.8
2.2
0.9
1.1
0.3
0.3
Darwin
3.0
3.7
0.9
1.1
0.4
0.5
Brisbane
2.6
3.1
1.0
1.2
0.3
0.4
Adelaide
2.4
2.9
1.3
1.5
0.5
0.5
Hobart
2.0
2.5
0.9
1.0
0.2
0.3
Melbourne
1.9
2.4
0.8
0.9
0.3
0.3
Perth
2.5
3.0
1.1
1.3
0.3
0.4
Canberra
1.9
2.3
0.6
0.8
0.1
0.2
Average
2.3
2.8
0.9
1.1
0.3
0.4
Given this performance at BCA2010 -70%, the Healthcare facility becomes increasingly dysfunctional in its energy use at BCA2010 -100%. As they already have deployed close to the maximum amount of PV, energy efficiency and trigeneration at -70%, the buildings need to purchase additional Green Power to reach the -100% level. As a result, no or few additional capital costs are incurred at this performance level. Despite this, the BCRs fall to very low levels (on average, around 0.4) due to the cost of Green Power purchases. Summary The general pattern of these results is that those buildings that are able to save the most electricity consumption (such as the supermarket – which is all-electric - and all buildings in cooling-dominated climates) tend to produce the most cost effective savings, as electricity is
31
around three times more expensive than gas. However, some buildings in cooler climates that save significant amounts of gas (for space heating and hot water) are also able to produce significant cost effective savings. Cost-effective savings are generally lower in Canberra than in other cooler climates due to the relatively low price of gas in the ACT. A further general driver of these results is that all these buildings are able to achieve at least 40% energy savings in most climate zones at quite modest incremental construction costs, of generally around 4% (6% - 7% for the 3-storey office). At these performance levels, none of the buildings adopt the more expensive solutions of cogeneration, trigeneration or photovoltaics, but rather rely on more efficient HVAC equipment, lighting systems and hot water, along with improvements to the thermal shells, deploying technologies that are generally well understood and readily available.
3.4 Break-even energy savings As described above, benefit cost ratios were calculated for each of the -40%, -70% and 100% performance levels (by building type and climate zone). Simple regression analysis was then undertaken to establish the break-even energy savings i.e BCR=1. On average, 68% energy savings are expected to be cost effective for commercial buildings by 2020 (see Table 14 below) relative to BCA2010. These results show a reasonable spread of results by climate zone, from Canberra at 54% to Darwin at 80%. Table 14: All Buildings- Break-even energy savings by Capital city, Year 2015
2020
Sydney
58%
68%
Darwin
74%
80%
Brisbane
70%
77%
Adelaide
67%
76%
Hobart
49%
61%
Melbourne
52%
63%
Perth
66%
75%
Canberra
41%
54%
Weighted Average
58%
68%
3.1 Benefit-Cost Analysis of PV in Commercial Buildings The results are not transparent as to whether PV is deployed at the break even performance level. Depending upon the building type and climate zone, PV is typically deployed at BCA 70% but not at BCA2010 –40%. When the break even performance level falls in between these two points, it is therefore ambiguous whether or not PV is deployed.
32
Table 15 below shows the projected cost effectiveness of PV for commercial buildings by climate zone. Future cost projections were based Raugei et al (2009). The benefit cost ratios are generally well below 1 except in Perth, where in 2020 it reaches 0.97. The breakeven results for commercial buildings are therefore largely insensitive to the presence or absence of PV. Table 15: Benefit Cost Ratios for PV- Commercial Buildings in 2020 Sydney
Darwin
Brisbane
Adelaide
Hobart
Melbourne
Perth
Canberra
0.56
0.62
0.61
0.75
0.57
0.56
0.97
0.44
4. Conclusion A critical driver of the results is the starting point implicit in BCA2010. The targeted BCR for commercial buildings in BCA2010 was 2, while the results in this study imply an even higher starting point. Such high BCRs indicate that many highly cost-effective energy savings options for commercial buildings were not captured in BCA2010. As a result, these savings opportunities remain available, and this significantly increases the overall level of savings that are now available at the break-even level of cost effectiveness. In addition, energy prices for electricity and gas, and also the mix of fuels used in different building types and climate zones, also impact upon the results. Fuel mix is also important. For example, allelectrical buildings in Darwin tend to have higher cost effective savings than buildings with significant gas use (normally in cooler climates such as Canberra and Melbourne), given the lower cost per GJ of gas. Also, supermarkets in this study are all electrical buildings, and this is one factor that contributes to the high level of cost effective savings in this building type.
5. References Australian Building Codes Board 2010, BCA 2010 Vol 1 : Building Code of Australia, Australian Building Codes Board. COAG (2009) National Strategy on Energy Efficiency. Commonwealth of Australia. July 2009.
Partridge L, Evans S, Augros R (2008) “Impact of Climate Change on Healthcare Facilities Management Delivery”, Ecolibrium : August, p26-32. Raugei, Marco and Paolo Frankl (2009). Life Cycle Impacts and Costs of Photovoltaic Systems: Current state of the art and future outlooks. Energy 34: 392–399.
33
The Treasury, Strong Growth, Low Pollution: Commonwealth of Australia, 2011.
modelling a carbon price:
update,
34
Cost Effective Energy Savings in Australian Houses to 2020 Tony Marker1, Robert Foster2, Phil Mcleod3 Abstract This paper analyses the level of cost-effective energy savings that new residential buildings could achieve in Australia by 2015 and 2020, relative to buildings compliant with the energy standards in the 2010 Building Code of Australia (BCA2010). It draws on research undertaken by the authors for the Australian Government (Department of Climate Change & Energy Efficiency). Twelve different residential building forms/construction types were modelled in each capital city climate zone in Australia. Cost effectiveness in this study was defined as a social benefit cost ratio of at least unity at a 7% real discount rate. The results show that on average, building shell thermal performance improvements and more efficient fixed appliances provide only modest cost effective energy savings by 2020, but there is significant variation in cost effective energy savings by climate zone. However, the results change dramatically when photovoltaics (PV) are included as part of the energy saving solution. Zero net energy for new residential buildings is shown to be cost effective by 2020 in all capital city climate zones, and even by 2015 in most climate zones. It was found that the key factors influencing the results are (1) the expected prices of electricity and gas in each climate zone over time, as these determine the economic value of the energy savings; (2) the differences in climates, as the severity of winter/summer conditions influence the total energy demand for space-conditioning purposes, and therefore the benefits of improving thermal shell performance; (3) the cost of achieving given levels of improvements in the building shell (in turn reflecting differences in construction techniques and distribution of residential building types by state/territory); (4) the cost of achieving energy efficiency improvements in the fixed appliances, such as hot water, lighting and pool pumps (which also vary by state/territory including due to differences in the starting point distribution of hot water appliance types in particular, e.g., solar, electric storage, gas storage, instantaneous gas, etc); (5) the ‘starting point’ energy efficiency (e.g., 6 star houses required in BCA2010); and (6) whether or not PV is allowed as part of the building solution. Keywords: Residential buildings, cost effectiveness, energy savings
1
Senior Consultant, Pitt&Sherry, GPO Box 94, Hobart TAS 7000 Principal, Energy Efficient Strategies, PO Box 515, Warrugul VIC 3820 3 Consultant, Pitt&Sherry, GPO Box 94, Hobart TAS 7000 2
35
1. Study Background This paper reports the results of analysis of the cost effectiveness of possible future improvements in the energy performance requirements of the Building Code of Australia, compared to current residential energy requirements introduced in 2010 (BCA 2010). The study was commissioned by the Commonwealth Department of Climate Change Energy Efficiency as a contribution to the National Building Energy Standard-Setting, Assessment and Rating Framework measure described in the National Strategy on Energy Efficiency (NSEE), which was approved by the Council of Australian Governments (COAG) in July 2009 (COAG 2009). The COAG Framework aims inter alia to lay out a pathway for future stringency increases in the Building Code of Australia (BCA) to 2020, in order to increase certainty for stakeholders and to facilitate strategic planning and innovation by industry. The study commenced in the first half of 2011, and initial assumptions on gas electricity prices were revised in late 2011. It should also be noted that assumptions on photovoltaic costs are in hindsight conservative, with costs having fallen more dramatically than assumed in the modelling.
2. Approach The study comprised four key steps. First, twelve different and representative residential buildings were identified and their energy performance simulated at a range of performance levels in each capital city in Australia. The performance levels begin with BCA2010 as a Base Case (not including any jurisdictional variations), and then move through successively challenging energy performance levels: BCA2010 –40%, BCA2010 –70% and BCA2010 – 100%, or zero net energy buildings. Second, independent estimates of the costs of these buildings at each performance level were provided by quantity surveyors, Davis Langdon, and also by Dr Mark Snow, a leading expert on building-integrated photovoltaics (BiPV), specifically with respect to PV system costs. This enabled the incremental cost of achieving the higher energy performance levels to be calculated with some precision, using conventional costing approaches routinely employed for building commissions in Australia. Third, benefit cost and break even analysis was carried out for each building type, climate zone, and performance level. For this analysis, the Base Case reflects the decisions announced in the Government’s Clean Energy Package and underpinning Treasury modelling (2011), including a carbon price of $23/t in 2012 rising at 2.5% (in real terms) per year for two years and then assumed to increase 4% per year. (3) The Base Case also assumes a rate of industry learning (how rapidly the real incremental cost of complying with new performance requirements declines through time) of 30% over 10 years, and a real discount rate of 7%. All buildings are assumed to have an economic life of 40 years and the benefit cost analysis is conducted over this period. It is important to note that the economic analysis in this report is based on energy required for space conditioning, hot water, lighting and swimming pool
36
pumps – all of which are subject to regulation in BCA2010. Like conditioning energy, the energy requirements for hot water and pool pumps are climate sensitive.
3. Energy and Economic Modelling Details 3.1 Building Stock There are significant differences between climate zones in terms of the distribution of construction types and, to a lesser extent, the prevalence of detached and semi-detached houses and flats. For example, medium-sized detached houses with brick veneer walls and concrete slab on ground (CSOG) represent over 50% of the current housing stock in the ACT and SA, but only 11% in NT and just 6% in WA. Cavity brick walls feature in over 70% of the housing stock in WA and 40% in NT (EES 2008). These differences affect both the potential for realising energy efficiency gains in the new housing stock and the costs of doing so in particular locations. The varying composition of the housing stock is taken into account when weighting results in this Report. The results for each individual climate zone are the weighted averages of the results for that climate zone of the 12 building types modelled, with weightings for each climate zone based on ABS building stock surveys reflecting the prevalence of each building type in the state stock. Full details of the construction types are available in the full study report.4
3.2 Building Improvement Cost Estimates and Assumed Learning Rates An independent quantity surveyor, Davis Langdon (an AECOM company), was retained to provide robust estimates of the costs associated with achieving the different energy performance levels for each building type for key building elements (Full details can be found in the full study report). Regional variations in the costs of plant and materials, as well as climate zone based variations in the building specifications, were taken into account. This analysis generated, firstly, robust estimates of the total costs of each building type in each climate zone as specified to comply with the BCA2010 Base Case (noting that this version of the Code is not yet in force for all building types in all states/territories). Secondly, the analysis provided a commercially-relevant incremental cost to be established for improving each building type to the required 40%, 70% and 100% energy savings relative to BCA2010. Learning rates were modelled by assuming reductions in the real costs of building materials used to reduce future energy costs for the Base Case (15% by 2015, 30% by 2020). The cost reduction is meant to encompass reduced labour costs resulting from learning, lower
4
http://www.climatechange.gov.au/publications/nbf/pathway2020-increased-stringency-in-buildingstandards.aspx
37
manufacturing costs from scale economies and market competition, and new technology developments that offer equivalent outcomes at lower costs.
3.3 Photovoltaic Cost Estimates Dr Mark Snow, an Australian expert on applications of PV to buildings, provided PV system output (solar yield by location with standard orientation) and cost data. It was assumed that residential buildings would use standard PV modules rack mounted on the roof (rather than integrated as part of the roof or façade). Using current technology, the area required for 1kWpeak mono-crystalline module (m-Si) system with 15% efficiency is 7m². However, module efficiency is expected to improve in the future, thus reducing the area required for a 1kWp system over time. This approach simplified cost estimates, though at the time it was recognised that rapid market and technology improvements made cost forecasts rather difficult. The cost estimate was based on a turnkey approach per 1kWp, and did not include any government subsidy through the RET/SRES certificates. Table 1: Cost of 1kWp PV system (standard PV modules) 2010-2020
Turnkey price (AU$/kWp) Standard PV modules
2010
2015
2020
AU$/kWp
AU$/kWp
AU$/kWp
$5,950
$4,400
$2,990
From the perspective of 2013 these are very conservative estimates, and single per kWp prices do not recognise scale economies from purchase of larger systems. In subsequent modelling, the discrete nature of PV is recognised by limiting PV additions to the nearest 0.1kWp required to deliver an appropriate reduction in utility energy. In subsequent economic modelling, it is assumed that PV systems are replaced after 20 years and inverters are replaced after 10 years. It is assumed that in all jurisdictions that net PV pricing is applied – that is, householders receive a price from utilities for each kWh generated by PV that equals the cost per kWh, without any feed-in tariff.
3.4 Energy Modelling and Climates All energy modelling was undertaken with the AccuRate energy modelling software, which includes 69 separate climate zones across Australia, and a much finer delineation of energy performance requirements than the 8 climate zones relevant to deemed-to-satisfy (DTS) requirements in the BCA. Energy efficiency performance standards in BCA2010 are defined in terms of DTS construction requirements, or modelled energy performance that equates to AccuRate 6-Star performance, expressed as total conditioning energy in MJ/m2 of conditioned space. In addition, BCA2010 contains requirements relating to hot water system efficiency, lighting requirements, and pool pump performance. Full details of the residential energy modelling can be found in the full study report. The sensitivity of 6-Star energy performance to climate can be seen in Table 2. Note that the Sydney climate used is Richmond, which is relevant to residential land developments in
38
Western Sydney rather than to coastal areas of Sydney. The climates range from tropical (Darwin) through relatively mild climates to the heating dominated climates of Melbourne, Hobart, and Melbourne. Table 2: Residential Space Conditioning Energy Requirements (MJ/m2.a) by AccuRate Star Band and Climate Zone 5 star
6 star
7 star
8 star
9 star
10 star
Sydney (West)
112
87
66
44
23
7
Melbourne
165
125
91
58
27
1
Brisbane
55
43
34
25
17
10
Adelaide
125
96
70
46
22
3
Perth
89
70
52
34
17
4
Hobart
202
155
113
71
31
0
Darwin
413
349
285
222
140
119
Canberra
216
165
120
77
35
2
The 10-Star performance is virtually zero conditioning energy, except for removal of latent heat due to humid air. Prior to BCA2010, many jurisdictions had set energy performance standards at the 5-Star level. The step from 5- to 6-Star represented a typical energy performance improvement of 20-25%. The specific requirements of the study required modelling 40% and 70% reductions in energy consumption – significant steps to ~7.5- and 8.5-Stars, respectively.
3.5 Energy and Carbon Prices Electricity prices were constructed as the sum of major cost components, comprising wholesale costs, network (transmission and distribution) cost, operating costs, and retail margin. Real network costs were assumed to increase by 1% per year to 2020, and remain constant thereafter. Retail operating costs, derived from the cost component data, are assumed to remain constant in real terms throughout the projection period. The wholesale cost component was calculated as the sum of two sub-components. The lesser subcomponent is costs other than the direct cost of purchased electricity and the major subcomponent is the average pool price of sent out cost of electricity generated. The approach used to construct projected natural gas prices was similar to that used for electricity. For this analysis, energy prices reflect the decisions announced in the Government’s Clean Energy Package (2011) and underpinning Treasury modelling, including a carbon price of $23/t in 2012 rising at 2.5% (in real terms) per year for two years and then assumed to increase 4% per year. It is important to note that both electricity and gas prices vary significantly by climate zone (see Table 3). Those climate zones with higher electricity or gas prices tend to show more cost effective savings. These two factors interact so that, for example, Darwin has a high use of electricity (natural gas is not reticulated in Darwin) but a relatively low electricity price.
39
These two effects tend to cancel each other out, leading to modest savings being reported for Darwin residential buildings. Table 3: Gas and Electricity Retail Prices (real 2012 prices) - Residential Sector in 2020, by Climate Zone Sydney
Melbourne
Brisbane
Adelaide
Perth
Hobart
Gas ($/GJ)
21.1
17.6
31.4
19.2
28.4
26.1
Electricity ($/GJ)
60.6
62.3
66.7
78.2
70.7
65.4
Darwin
Canberra 23.2
54.9
46.9
3.6 Economic Modelling The benefit cost analysis considers the value of (purchased) energy savings over an assumed 40 year building life arising from the higher energy performance requirements modelled, compared to the energy costs that would have been incurred had the same buildings been constructed to BCA2010. This means, for instance, that energy derived from a building’s PV installation is represented as a reduced requirement for purchased electricity. Separate calculations are made for each scenario, building type, climate zone and performance level, for each of the 40 years of building use after construction in 2015 or 2020. The energy savings are measured in annual MJ/dwelling for residential buildings. Electricity and gas are treated separately, and use of minor fuels (e.g., wood, LPG) is also measured for residential buildings and is taken into account in the benefit cost analysis. All prices and costs are represented as real 2012 prices, so that the effect of inflation is excluded. Finally, it should be recalled that the energy costs considered for these buildings exclude those costs associated with internal appliances and equipment (‘plug load’) that are not currently regulated by the BCA, including cooking energy. The exception to this rule is for the -100% or ‘zero net energy’ buildings, where the study required inclusion of the plug load and cooking energy. This has the effect of increasing the incremental costs of this solution, when compared to the other performance levels targeted, as the PV system has to be sized to also cover the plug load and cooking energy. The value of future energy savings and incremental costs are discounted back to a present value. The primary rationale for discounting is the observation that people display ‘time preference’; that is, a dollar today (of benefit or cost) tends to be valued more highly than a dollar in the future. This effect is reinforced by the ‘opportunity cost of money’, which in effect is defined by the real interest rate. That is, one can choose to spend a dollar today or next year, but the value of the dollar next year is increased by the real interest rate available. In effect, the real interest rate represents the amount that must be offered to induce someone to defer the value of present consumption. In this way, the real interest rate is taken as a working proxy for the time value of money.
40
The Office of Best Practice Regulation requires a 7% real interest rate to be used for present value calculations for regulatory analysis. Energy savings at break-even and at 40%, 70% and 100% have been calculated using a 7% discount rate. It may be noted that this is considerably higher than current real interest rates in Australia, and relatively high for long lived assets.
4. Modelling Results The starting point stringency of the energy provisions in BCA2010 (6-Star) is a factor that could be expected to influence the overall level of future cost effective savings. The Regulatory Impact Statement (RIS) on the introduction of 6-star into the BCA indicated that it was marginally cost effective on an Australia average basis. This tends to limit the scope for further cost effective savings beyond that level - at least, in the absence of PV, as discussed below.
4.1 Impact of PV Where PV is allowed as part of the building solution, it has a dramatic effect on the breakeven level of energy savings reported, and results are presented below on a without/with PV basis. Where, for a given climate zone, PV becomes cost effective in its own right, then the break even energy savings for residential buildings in that climate zone becomes 100%. This is because any level of residual energy demand can be covered cost effectively by the PV system due to the scalability of PV systems to any size through the addition of extra modules and components, subject only to physical constraints such as suitable roof area and the capital cost. The results without PV are driven by the cost effectiveness of: a) improvements to the thermal shells, and; b) improvements to fixed appliances. In this study, PV systems were treated as if they were another ‘fixed appliance’ which may be traded off against efficiency gains in the thermal shell and those fixed appliances already regulated by the BCA (hot water, lighting, pool pumps) in determining a least cost mix of measures that provide at least break-even benefits (BCR = 1.0). We therefore analysed the cost effectiveness of PV systems in each climate zone, taking into account the differences in electricity prices and PV yield by climate zone. As previously discussed, the cost of PV is projected to fall dramatically into the future. The most significant price reduction is occurring for the cost of panels (and to a lesser extent for inverters). While these costs currently represent a large share (60+%, depending on total installed capacity) of the current total cost of the turnkey price of a solar energy installation, there is no certainty about future market prices of these components in Australia. The capital cost assumes a 20-year life for the PV panels and replacement of the inverter after 10 years, both of which are conservative. Table 4 shows the resulting benefit cost ratios (BCRs) for residential PV systems. It can be seen that in 2020 PV is cost effective in all climates. All the economic modelling for residential buildings is based upon improvements being added to dwellings in order of declining BCRs until the break even or specified energy reduction is achieved. This means
41
that building shell or other improvements are made up to the point when the BCR of PV is reached but no further. Moreover, when the BCR >1 for PV, any required level of energy reduction can be achieved cost effectively (i.e. above breakeven), although not necessarily at low absolute cost. Further, there may be a practical limit in terms of suitably oriented and unshaded roof area for real dwellings, which has not been explicitly taken into account in the modelling. Table 4: BCRs for Residential PV by Climate Zone Sydney West
Darwin
Brisbane
Adelaide
Hobart
Melbourne
Perth
Canberra
2015
1.01
1.07
1.12
1.36
1.01
0.98
1.39
0.77
2020
1.41
1.47
1.57
1.89
1.41
1.37
1.96
1.09
4.2 Break Even Energy Savings Table 5 shows the energy savings at break even for the Base Case compared to the same buildings constructed according to the energy performance requirements of BCA2010. The energy savings from reductions in space conditioning and fixed appliance (hot water, lighting, pool) energy are expressed as reductions from BCA2010 performance. The building shell rating (in AccuRate stars) indicates that most energy savings relate to improved performance of fixed appliances and not improvements in the building shell. The 6-star building shell performance means that in mild climates (Brisbane, Perth, Sydney, Adelaide) the space conditioning energy requirement is small both in absolute terms and as a share of total energy consumption (excluding plug load and cooking which is not regulated under the BCA). As a result, there is relatively little space conditioning energy remaining to save in these climates and there are very few improvements that can be shown to be costeffective for these climate zones. By contrast, in the locations with the highest space energy requirements (Canberra, Melbourne and Hobart) some improvements in the building shell performance are cost effective in this scenario. Table 5: Break Even Energy Savings Relative to BCA2010, All Residential Buildings, Without PV, Base Case, 7% Real Discount Rate Space Conditioning and Fixed Appliance Savings
2015
2020
2020 Break Even Thermal Shell Star # Rating
2020 Space Conditioning Energy
2020 Space Conditioning Energy at Break Even
Sydney West (CZ6)
9%
14%
6.0
30%
4.7GJ
Darwin (CZ1)
3%
3%
6.0
69%
17.3GJ
Brisbane (CZ2)
7%
7%
6.0
20%
1.6GJ
Adelaide (CZ5)
11%
11%
6.0
45%
6.9GJ
Hobart (CZ7)
14%
17%
6.4
67%
18.3GJ
42
Melbourne (CZ6)
3%
7%
6.2
66%
21.8GJ
Perth (CZ5)
18%
32%
6.0
29%
2.8GJ
Canberra (CZ7)
4%
7%
6.2
70%
26.8GJ
Notes: # = composite star rating for Class 1 (detached) and Class 2 (flats) buildings. Space conditioning energy consumption is shown in Column 5 as a percentage of total energy consumption excluding plug load and cooking energy then, in Column 6, in absolute terms.
Additional sensitivity analysis around these ‘without PV’ results was undertaken to examine the impact of assuming a range of ‘no cost’ design changes to some of detached dwelling forms which resulted in building shell improvements in the range 0.2 – 0.9 stars (depending on climate). In such cases, the overall energy savings improved and the building shell rating at break-even also improved. When PV is added into the mix, the results change dramatically. Zero net energy housing is shown to be cost effective by 2020 in all climate zones studied. The cost of PV panels has declined dramatically in recent years and is projected to decline further by 2020. This combined with rising electricity prices is making the electricity produced from PV installations increasingly cost effective. Indeed by 2015, except for Melbourne and Canberra, PV installations are cost-effective in their own right, and by 2020 this is true for all climate zones. This means that essentially any level of energy savings, relative to BCA2010, is also cost effective when PV is allowed in the building solution - constrained only by physical considerations such as the area of North-facing roof upon which to mount PV systems. As soon as this condition occurs in a climate zone, the break even or cost effective level of energy savings immediately rises to 100% (i.e., zero net energy). Another way to interpret these results is to note that the various ‘treatments’ or upgrades that may be applied to a 6 star, BCA 2010 house have different costs and benefits. In our analysis, these treatments are selected in declining order of cost effectiveness (that is, the most cost effective are selected first). As soon as PV panels become the next most cost effective treatment, no further treatments (and hence no further costs) are required to reduce the house’s energy consumption to zero. While PV is a cost effective solution, the break even with PV results required 1.5 – 7.4kW of PV, with net present costs from $5,000 to $30,000.
4.3 Benefit Cost Analysis at Targeted Performance Levels Modelling was undertaken to determine the benefit cost ratios at reductions of 40% and 70% from the BCA 2010 level (covering the building shell, water heating, lighting and pool pumps). Additionally, at 100% reduction, a net zero energy solution was required in which all cooking and plug load energy was also offset by renewable energy. The results shown in Table 6 are the ‘without PV’ solutions. There are no cost effective solutions, with the best results occurring for the three cool climates. For both -70% and -100% energy reductions, the best results occur for Canberra at around 40% BCR. The results shown in Table 7 below are the ‘with PV’ solutions. All climates except Canberra and Melbourne have cost effective solutions for each energy reduction target. As soon as
43
other improvements with BCRs better than that of PV are exhausted, PV is then used to reach the required energy reduction at the BCR of the PV. If the BCR of PV exceeds break even, any level of energy reduction is possible at better than break even because of the scalability of PV systems. It should be noted, however, that the upfront cost of PV systems may be significant, even if they are cost effective: the current net present costs per kWp of PV installed are about $7,300, $4,900 and $3,600 (7% discount rate) in 2010, 2015, and 2020, respectively. It should also be noted that around 7m2 of appropriately oriented and un-shaded roof is required per 1kWp. Table 6: Benefit Cost Ratios without PV in Solution, at 40%, 70% and 100% Reduction from BCA2010 by Climate Zone, 7% Real Discount Rate -40%
-70%
100%
Climate Zone
2015
2020
2015
2020
2015
2020
Sydney
0.17
0.21
0.13
0.17
0.13
0.17
Darwin
0.25
0.31
0.24
0.31
0.24
0.31
Brisbane
0.35
0.41
0.10
0.12
0.10
0.12
Adelaide
0.25
0.33
0.16
0.21
0.16
0.21
Hobart
0.47
0.60
0.27
0.35
0.27
0.35
Melbourne
0.37
0.47
0.20
0.26
0.20
0.26
Perth
0.20
0.26
0.19
0.25
0.19
0.25
Canberra
0.40
0.55
0.30
0.41
0.31
0.42
Table 7: Benefit Cost Ratios with PV in Solution, at 40%, 70% and 100% Reduction from BCA2010 by Climate Zone -40%
-70%
-100%
Climate Zone
2015
2020
2015
2020
2015
2020
Sydney
1.03
1.43
1.02
1.43
1.01
1.42
Darwin
1.07
1.47
1.07
1.47
1.07
1.47
Brisbane
1.14
1.58
1.13
1.58
1.13
1.57
Adelaide
1.38
1.90
1.38
1.90
1.37
1.90
Hobart
1.10
1.53
1.05
1.47
1.03
1.44
Melbourne
0.98
1.38
0.98
1.37
0.98
1.37
Perth
1.43
1.99
1.41
1.98
1.40
1.97
Canberra
0.77
1.09
0.77
1.09
0.77
1.09
5. Sensitivity Analysis A sensitivity analysis was undertaken using a higher carbon price and a higher rate of industry learning. Table 8 below shows that the cost effective level of energy savings,
44
relative to BCA2010 and without PV, is significantly higher than in the Base Case, reaching 23% on a weighted average basis. The spread of results by climate zone continues to reflect differences in relative fuel prices, which are exacerbated by carbon pricing, increasing the relative attractiveness of electricity savings. Note that in Australian conditions, this result also leads to higher greenhouse gas emission savings than occur from savings of natural gas. Table 8: Break Even Energy Savings Relative to BCA2010, All Residential Buildings, Higher learning rate and higher carbon price, Without PV Scenario 2
Sydney West (CZ6)
2015
2020
2015
2020
@ 5%
@ 5%
@ 7%
@ 7%
19%
26%
14%
19%
Darwin (CZ1)
5%
23%
3%
15%
Brisbane (CZ2)
7%
30%
7%
22%
Adelaide (CZ5)
11%
22%
11%
22%
Hobart (CZ7)
19%
30%
16%
25%
Melbourne (CZ6)
13%
33%
4%
25%
Perth (CZ5)
32%
32%
26%
32%
Canberra (CZ7)
13%
43%
7%
29%
Weighted Average:
15%
30%
11%
23%
6. Conclusion The study demonstrates that there is limited scope to regulate further cost effective building shell improvements other than in the heating dominated cooler climates of southern Australia. Energy reductions of 1-Star (or ~30% below the BCA2010 6-Star level) would be cost effective. Such regulation would need to be applied by AccuRate Climate Zones rather than by the wider BCA climate zones or by jurisdiction with wide ranges of climates. It is clear that improvement of the current building shell performance level cannot cost effectively compete against future improvements of fixed appliances covered within the BCA. More significantly, PV as a fixed appliance with its output valued at the householders electricity tariff (net metering), is a more cost effective approach than building shell improvement for most of Australia. This is demonstrated by the conservative cost approach used for PV in the study undertaken in 2011 – from the perspective of 2013 PV makes an even more significant contribution to cost effective reduction of energy consumption and greenhouse gas emissions.
References Australian Building Codes Board (ABCB) (2010), BCA 2010 Vol 1 : Building Code of Australia, Australian Building Codes Board.
45
Council of Australian Governments (COAG) (2009), National Strategy on Energy Efficiency Commonwealth of Australia. Energy Efficient Strategies (2008). Energy use in the Australian residential sector 19862020: Final report for Department of the Environment, Water, Heritage and the Arts, Canberra The Treasury (2011), Strong Growth, Low Pollution: modelling a carbon price: update, Commonwealth of Australia, Canberra
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Life Cycle Energy Analysis of Residential Building Retrofits Incorporating Social Influences Melissa Gaspari1 Abstract Retrofitting is a front-runner in sustainable options to improve residential lifecycle energy consumption as Australia’s home energy use rises. Over the past 20 years there has been a growing trend for larger houses within Australia; combined with the residential sector being responsible for 7% of Australia’s energy use, the need to improve our current housing stock is hard to ignore. The average household is overrun by various rebates, technology, and fashionable quick fixes to improve their home’s energy efficiency, but how do these households choose? This paper explores the way Life Cycle Energy Analysis supports decision-making when retrofitting for energy efficiency and incorporates how social influences, such as age, income, goals, time constraints, thermal comfort, gender and technology factor into the way homeowners prioritise their retrofitting options. Current research identifies many different approaches to using Life Cycle Analysis to support decision-making in retrofitting. However, few have addressed the influence of social aspects. This research incorporates the human and social aspects into a decision-support framework. This framework uses Life Cycle Energy Analysis as a tool to support decisionmaking and intends to identify a means to align the most effective life cycle improvements to the social intentions, objectives and constraints of homeowners. Using information gathered from interviews with over 10 different homeowners, the framework integrates the real life scenarios to outline the social effects, whilst simultaneously allowing homeowners to meet their needs and still consider energy efficiencies and improvements over the lifetime of their home. To fill the gap in connecting social aspects with lifecycle decision-making this paper is designed to incorporate energy efficiency into the decision matrix using Life Cycle Energy Analysis, while supporting the social objectives of homeowners over the entire lifecycle of an Australian residential building. Keywords: Sustainability, Life Cycle Energy Analysis, Social Influences, Retrofit, Residential.
1
Graduate Honours Student; University of Wollongong; 59/6-10 Eyre Street Griffith, ACT 2603;
[email protected]
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1. Retrofitting Residential Buildings Retrofitting is an attractive option to improve residential life cycle energy consumption in Australia; it is an emerging industry helping to determine how the energy use of an existing home can be reduced. This concept of building retrofit is more commonly seen in commercial buildings, and has been proven to lead to considerable reductions in energy use (Yohanis and Norton, 2002). Life Cycle Analysis (LCA) is one technique to assess the environmental aspects and potential impacts of products from raw materials to production, end use and disposal (Australia/New Zealand Standard, 1998). Life Cycle Energy Analysis (LCEA) uses this same approach with energy being the only indicator. One of the key components of a LCEA is embodied energy. That is, the energy used in the production of the materials and a significant contributor to the amount of energy used to complete a retrofit (Hogan, 2011). For this reason, studying the outcomes of LCEA of retrofit options should include embodied energy, operating energy (the energy consumed during a buildings lifecycle), as well as maintenance and disposal energies, in order to provide a complete insight into the most energy efficient options. LCEA may be used to assist in decision-making for many factors including social influences and gives a comprehensive cradle-to-grave appraisal (Australia/New Zealand Standard, 1998). The existing housing stock in Australia requires significant retrofit as it currently threatens to be the biggest liability in long-term energy efficiencies. Approximately 2% of new housing is constructed each year in Australia, leaving 98% of the existing housing stock to be retrofitting or retired (Department of the Environment, 2008). Of this only approximately 80% of housing is occupied –3.3% of which is already undergoing retrofit or renovation and only 1% is being retired - leaving over 75% of the existing housing market open to some form of energy retrofit and improvement (Department of the Environment, 2008). Behavioural attitudes, climate, housing size, occupancy, level of education and other social influences affect the overall energy consumption of a home, and although some homes may be deemed to require energy retrofit, they may consume less energy in their operation than others due to their occupants. Climate zones offer static parameters and many retrofitting options can be used across multiple climate zones, highlighting that behavioural attitudes or social influences will have the greatest impact on results. The most effective retrofit options are limited without knowing the exact conditions of the existing housing stock that requires retrofitting. The implications of social factors in this study will be the most notable, as they will provide an insight into decision-support of retrofitting options. LCEA can incorporate these parameters to provide a whole of life evaluation, providing an insight into retrofitting options for the existing Australian housing stock.
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1.1 LCEA as a decision support tool for building retrofitting A recent study, Comparing life cycle implications of building retrofit and replacement options, discusses the question of when it is best to retrofit a building rather than rebuilding it (Dong, Kennedy et al., 2005). Typically, LCEA models and tools are aimed towards improvements in design of new dwellings. However, with the large stock of existing residential buildings, this attention has recently shifted toward energy retrofit (Dong, Kennedy et al., 2005). To analyse a whole of life approach Dong, Kennedy et al., (2005) use a LCEA methodology, with a series of environmental indicators, (global warming potential, waste, water pollution, cost, economic indicators as well as energy), highlighting the parameters and context of this LCEA. LCEA supports the decision-making process in this analysis, as the conclusions of this study show that, despite the high energy saving in rebuilding at any one stage, the waste produced by this process is severe. This concludes that in the context of one of the indicators, waste, the views of LCEA can be altered and the impacts varied from the initial energy assessment. Reductions in both embodied energy and operational energy need to be balanced in order to identify the whole life cycle energy efficiencies. When determining retrofit options, indicators provide alternative ways of analysing this balance. LCEA uses energy as the singular indicator in this balancing process. Ramesh, Prakash et al., (2010) emphasise this in their research of seventy-three case studies from thirteen different countries, considering the energy consumption of either conventional or low energy buildings. Their analysis of both the operating and embodied energy highlighting the significance each energy phase has on the overall building life cycle energy. This research indicates the usefulness of the LCEA approach in determining energy savings, and is paramount to the decision making processes. Trade-offs and balancing energy phases is crucial in LCEA.
1.2 Indicators for Life Cycle Energy Performance Indicators used for life cycle performance aid in determining environmental impacts. LCEA is rarely completed alone, often using key indicators, impact assessments, or characterisation factors to help identify the full influence of the choices at hand and the long-term effects. Existing research presents a number of commonly used indicators and impact assessments, as per AS/NZS ISO 14042,yet for the purpose of this research, indicators that will be used in the decision making process, will be social influences and energy. Research completed by Peter Clinch and Healy (2003) explore the single factor of comfort, which focuses on LCEA of energy-efficient retrofits in Ireland. This research further defines the limitations and impacts of this indicator (comfort). Peter Clinch and Healy (2003) discusses the clear trade off indicators create, most importantly illustrating the limitations of various indicators and factors in their analysis. Emphasising the individualistic nature of home ownership and retrofit decisions, Peter Clinch and Healy (2003) conclude that dependant on these individual characteristics, what may have initially been retrofit for
49
energy, may not decrease energy consumption, but instead, increase comfort (or an alternative factor). One key perspective that needs to be considered is the national code of building construction, known as the Building Code of Australia (BCA). Morrissey and Horne (2011) suggest that the minimum standards set in the BCA do not necessarily promote the most cost effective options available when constructing a home, or updating an existing home to meet the current standard. Although the BCA sets the minimum code for energy efficiency, it is suggested that LCEA combined with exceeding the BCA requirements provides a more cost effective energy choice for a greater time period (Morrissey and Horne, 2011). From these studies, it is clear that indicators, factors and characteristics beyond energy, including environmental impact factors (such as CO2, pollution, waste), and most significantly regulations and social influences, play a vital role in supporting and assisting decision-making in the retrofit area, as well as illustrating a more accurate understanding of energy efficient retrofits, trade-offs and impacts of a residential buildings lifecycle.
1.3 Retrofit for climate and LCEA One key element common to all studies is climate. Fay, Trealoar et al. (2000) discuss the relevance of temperate areas and the affect this has on the embodied energy, suggesting that the LCEA of dwellings in temperate zones, such as those analysed in this paper, will gain significant operational savings but suffer high-embodied energy. Dong, Kennedy et al. (2005) support this in their conclusions, as in the Canadian climate of Toronto, the energy efficiency gain through operation outweighs the large embodied energy components. Whether embodied energy has a greater impact over operational energy is due to the heating and cooling requirements. A temperate climate has minimal heating and cooling requirements compared to those in more severe climatic zones. Using a breakdown of embodied energy, operational energy and maintenance energy, indicators and cost relevant to the identified climatic zone, energy components can be isolated and analysed against one another and as part of the overall assessment. Dong, Kennedy et al. (2005) also conclude that there is a trade-off for energy reduction within the separate phases and that the severity of other impacts should be analysed. The Australian Your Home Technical Manual (Reardon, Milne et al., 2010) categorises Australia’s overall climate into eight different climatic zones, from high humidity and warm winters to alpine winters and cooler summers. Australian housing must cater for varied climate conditions dependant on location. Falcone’s (2011) research in warmer climates is just one example of the impact climatic zones have on the boundaries and context of retrofitting options. Without the boundaries set by climate, retrofitting for energy efficiency is extremely unreliable. Therefore climate must be considered as an essential input in LCEA, as the energy efficiency gains are made to improve the energy consumption during the operation and use of a residential building and these are directly linked to climate requirements.
50
2. The Proposed Framework The framework of this study intends to support decision-making in retrofitting residential dwellings primarily analysing trade-off impacts from the available retrofit choices, the life cycle cost and the social impacts or influences of these choices. Figure 1 presents the high level framework, showing the relational dependencies of social influences when prioritising retrofitting options, and determining LCEA outcomes.
Retrofitting Options LCEA
Social Influences Figure 1 High Level Framework to using LCEA to support Retrofitting choices Any number of social influences can affect a homeowner or occupier when making choices related to energy within their home. The framework seen in Figure 2 suggests one approach for incorporating these social variables into specific retrofitting choices. It allows social factors to be identified and for physical factors (such as building age and condition) to be excluded as a social variable. This framework enables multiple social variables to be considered while still incorporating house specific details. It allows the LCA process to be seen through these social influences, as well as feed impacts of these choices back into the decision-making process. Further development of this framework would provide a comprehensive understanding of specific social influences; retrofitting options and choices that occur during energy related retrofitting of residential buildings.
2.1 Physical and Social Constraints for Retrofit Options Every retrofitting scenario is unique and varies based on constraints of each specific dwelling. Building age, condition, location, material make up, and historical significance are some examples of the constraints that determine feasible and available retrofitting choices. Together with the social context of the owners of the dwelling, these variables and constraints determine the priority of retrofitting choices. 2.1.1 Physical Constraints Different physical constraints influence retrofitting options in various ways; some by eliminating options and others by priority or lack of current techniques. However, physical constraints cannot be changed without some form of retrofit or renovation, and therefore have a significant impact. The type of building is also a key factor when identifying retrofit choices, and can immediately eliminate options for reasons such as accessibility. Climate and location are
51
also significant physical factors in building retrofit. Location often incorporates the features of climate as well as building location and orientation (including aspect); housing and population density; historical relevance; and other area constraints. For comprehensive Life Cycle Analysis to be completed, both physical variables and social variables need to be considered. Noting that social variables can be more flexible and vary through means of education, resource availability and incentives
Retrofitting Options LCA Methodology
Physical and Other Constraints House Condition, Building Age, Location, Climate, Visual Appeal, Restrictions due to historic relevance, Building Type
Retrofitting Option Decision Making Life Cycle Assessment for Retrofitting Options Life Cycle Inventory Analysis
Social Influences/Requirements Age
Embodied Energy
Flexibility, Health, Environment, Social Networks,
Operational Energy
Value for Money
CO2 Emissions
Operational Savings, Objectives, Budget, Investment, Income, Job
Improve Lifestyle Application of New Technology, Age of House, Priorities
Time Flexibility, Time Concerns, Location, Priorities, Social Relationships
Thermal Comfort and Resilience Thermal Comfort, Environment, Gender, Climate, Health
Alternative Environmental Results/Interpretation of LCEA, comparing cost effectiveness and energy efficiency against social requirements Integration with other performance indicators and regulatory compliance
Figure 2 Detailed Framework 2.1.2 Social Variables Social Variables defined as the personal influences on homeowners, such as age, gender, availability, education, any social influences on a homeowner that significantly affects the choices they make regarding their home. For the purpose of this research the identified framework will enable the use of social variables and themes identified in the pilot survey of
52
10 different homeowners. The purpose of the survey was to identify key social variables that influence each homeowner’s choice of retrofitting options. The survey specifically focused on homeowners from two separate age groups, those less than 30 years of age and those over 50 years of age, as they displayed often opposing views. Table 1 displays the extracted themes and key survey results. 2.1.3 Social Variables – Survey Methodology The survey was conducted by asking a series of closed questions regarding the social status of the participants, before open ending questions sort to establish participant understanding of terminology such as energy efficiency. Beyond this participants were asked to rank preferred retrofitting options and list key arguments to support this ranking. It was clear in the initial discussions, definitions of terminology pose the greatest risk when selecting retrofit options due to the differences in perceived and actual understanding. This survey regulated the variables of terminology, by stipulating each retrofitting option’s benefits, impacts on time and specifications. Participants were selected to ensure, they all originated from the same location, and created diversity in age and education, and involvement in energy efficiency practices for the small group of participants. Joint homeowners were considered and interviewed, as individuals to ensure definitions and education factors were not altered by joint ownership influence, or perceived understanding. The survey presents clear distinctions between younger and older generations and their understanding and perspective of retrofitting and energy efficiency. Younger generations showed a more comprehensive understanding of the diversities within energy efficiencies and options for improvements; whereas, older generations highly regarded maintenance to improve energy use. Younger generations were also more likely to retrofit solely for energy improvements, even replacing working appliances or components; whereas older generations preferred to maintain items for longer and then replace them at the end of their useful life with the most efficient technology. This concept is evident in each age group’s readiness to prioritise energy retrofit over other improvements. Social variables assist in pre-defining the needs of individuals and available retrofit options, prior to completing LCEA. However, they also assist in post-LCEA, where individuals can assess the social influences in conjunction with the whole of life results for any singular retrofit option. The social variables outline the priority of retrofitting options under specific social influences (in this research age was most dominant). This highlights that despite the comprehensive understanding of the whole of life efficiencies LCEA demonstrates, it is overshadowed by individual preference dominated by their social influences, outcomes and objectives.
2.2 Retrofitting Options Varying age groups and building constraints determine various retrofitting options. The retrofitting options considered for this research can be seen in Table 1 and are prioritised by the age of households, specifically the two age groups that identified to have the most common trends. Different aged households have diverse priorities and these priorities
53
determine the best retrofitting choices for each social perspective. These are the perspectives that will be tested through LCEA to determine if the social requirements of either group to achieve greater energy improvements. Table 1 Modelling Parameters Used in Accurate or LCADesign Software and Priority of Age Group Product
Modelled as
Priority Priority 50 (6 being top priority, 0 being least priority)
Replace Single Low U-Value, Mid range Modelled as Double Glazing with 4 Glazing with Solar Heat Gain Coefficient, a 6mm air gap between high Double Glazing Season Specific Shading performance glasses. Windows
1
Installing Wall Achieve an R-value of 2.8 Insulation
Modelled with an R-value of 5 greater than 3.5 regardless of material selection/material type
0
Installing Ceiling Achieve an R-value of 2.8 for Modelled with an R-value of 5 and Wall walls and 4.1 for ceiling greater than 3.5 regardless of Insulation material selection/material type
0
Installing Floor Achieve an R-value of 1.25 Modelled as plastic sheeting 5 Insulation (expect for slabs on ground) between floor slab and ground; or in suspended floor with R-value greater than 3.5 regardless of material selection/type
0
Installation of Installation of foam/rubber Not modelled; taken various Air- compression material, draft literature or negligible Sealing protection on doors, self techniques closing doors, exhaust fans fittings with a flap/dampener
from 2
4
1
3
Installation of Low U-Value, Mid range Modelled as Double Glazing with 0 Skylights to Solar Heat Gain Coefficient, a 6mm air gap between high reduce artificial Season Specific Shading performance glasses. lighting
0
Replacement of Appliances to all 3.5 stars or above
Modelled as appliances with 3.5 0 star rating or where no half star available 4 star rating
5
Replace heating water
Modelled as single solar panel, 0 with 0.75 efficiency
2
Installation of Add shading either devices Not Modelled various Shading or deciduous trees to Devices prevent summer sun and aid winter light
solar for
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2.2.1 LCEA Decision Support Tool LCEA can be used as a decision support tool when comparing available retrofitting options. The most significant of advantages is ability to use LCEA to give a whole of life understanding of energy uses and demands. This is the process that software packages will be used to calculate in order to determine embodied and operational energy used over the lifetime of a case study. 2.2.2 Embodied Energy – LCADesign For the calculation of embodied energy LCADesign and Building Information Models were used to assess the total embodied energy of the base case studies as well as retrofitting scenarios. LCADesign is a software tool used to analyse and assess the embodied energy of a building. By using Building Information Models, LCADesign can comprehensively assess the embodied energy of the components used to construct a building. Each material can be ‘tagged’, identifying it from the Australian specific Life Cycle Inventory. Analysis for a single dwelling can be run with multiple inventory models, allowing comparison between retrofit options. 2.2.3 Operational Energy – AccuRate Sustainability For the calculation of Operational Energy, AccuRate Sustainability was used. AccuRate Sustainability is currently one of the software products recommended by Australian Government when assessing a dwelling’s star rating. AccuRate Sustainability predicts the required operational energy consumption for one year given building parameters. Building parameters required include occupancy, room size, volume and orientation, hot water heating, lighting and water sources. AccuRate Sustainability provides star rating indicators, energy consumption in Mega Joules/area, as well as water heating energy and water consumption assessment. Other indicators can be assessed from both software packages, such as water usage, gas usage, as well as other environmental factors, including CO2 and Greenhouse gas emissions. For the purpose of LCEA, energy is the primary indicator, however there are a number of alternative software packages that take these environmental factors into consideration beyond LCADesign and AccuRate Sustainability, but are beyond the bounds of this research.
2.3 Findings and Discussion 2.3.1 LCEA and Social Influences In the case studies tested, the operational energy decrease appears to coincide with embodied energy increase, with the introduction of new materials. Embodied energy does not accurately reflect the reasons to retrofit, objectives or retrofitting priorities of homeowners. In understanding the trade-off between this increase and the operational energy benefit to be gained we can begin to deduct the social impacts of these results.
55
Younger generations’ choices are fuelled by their objectives to reduce their environmental footprint and consumption, something not reflected in their reasoning when choosing a retrofit option. When prioritizing the available retrofitting options, younger people chose options that reflected their objectives and offered large operational energy savings, with high embodied energy costs. These choices, however, resulted in a life cycle energy reduction, improving the energy efficiency of their home. Despite younger people’s comments regarding limited budgets and significant time constraints, they prioritised retrofitting choices that met their objectives before other choices. Older generations’ reasons to retrofit, objectives and retrofitting priorities were very much in line with one another, indicating a clear understanding of their goals when it comes to retrofitting their homes. Their choices reflected their time and budget constraints and their understanding of the impact of retrofitting on their daily lives. Unlike younger people, their choices did not have large operational savings, or high embodied energy, instead they offered a more diverse consumption reduction, indicating that a LCEA cannot assess the total environmental impact of their choices. It is clear that for the survey group in this study that their retrofitting priorities were based very much on their overall objectives for their homes rather than their reasoning to retrofit, these objectives reflected high-level thinking and goals, as opposed to lower level outcomes. The younger age group chose better retrofitting options in terms of LCEA, as they opted for retrofitting priorities, which significantly reduced their energy consumption. This suggests that in isolation LCEA shows younger generations make more effective choices, however does not fully consider all environmental impacts that are affected by these choices. Older generations choices reflect a broader perspective on energy efficiency and environmental sustainability that LCEA does not adequately measure or account for in this research. LCEA supports decision-making with respect to energy consumption, and this whole of life view is crucial in understanding what energy trade-offs are made with each retrofitting decision. Assessing the social influences on retrofitting options through LCEA gives a clear understanding that most retrofitting options will improve the life cycle energy of a home. However, it does not fully assess the environmental impacts beyond energy demand, and this can be seen as one of its greatest limitations. 2.3.2 Limitations There are a number of limitations to this research. The pilot survey conducted was limited to a specific climate zone, and sought out particular participants, those in a position to retrofit. Due to the small sample size, it is hard to ascertain key trends beyond the two age groups listed and their key objectives and retrofitting priorities. Presenting the results on the clearest trends in data has mitigated this limitation. The Life Cycle Inventories used, were based on assumptions from software developers. The software programs offer only a single Life Cycle Inventory (LCADesign) and have their own methodologies and frameworks for the calculations used to simulate energy performance.
56
The development of Australian Life Cycle Inventory Data is limited by the research available for each individual product and, therefore, retrofitting options such as appliances cannot be fully assessed via simulation.
Conclusions The framework presented in this research has highlighted a number of areas for further development and research to complete a comprehensive understanding of the social influences that affect retrofitting options. Operational energy is the largest consumer in Life Cycle Energy accounting for approximately 80% of the total Life Cycle Energy demand. Reducing this operational energy is the largest trade-off when making retrofitting decisions, regardless of social influences present. There are key limitations and gaps in the current research regarding common household appliances and how they can be used to reduce energy. Capturing these reductions in energy, from appliances, such as water heaters, dishwashers, and TV’s, can help to assess the impact of purchasing higher rated appliances. Social consumerism is already prominent in many appliances, with star rating systems in place. However, there is a lack of integration between these star ratings and the total impact on the life cycle energy of a residential building. Similarly, little is understood about the impact of appliances on embodied energy of a residential building, despite an understanding of the impact of these individual products. The results presented indicate, even with large embodied energy increases from the introduction of further materials, the operational energy savings is decreased significantly, often outweighing the impact of embodied energy on the total life cycle. This currently is not the case for appliances, or solar heating. Social Influences pose the biggest threat to reducing residential buildings energy impacts. Social Influences affect not only the choices homeowners make when retrofitting, but also, how they make these choices. The survey completed in this research is applicable to many retrofitting scenarios and further analysis from the data available could present further trends in this particular set of scenarios. Understanding the motivation behind the choices made by various social groups allows a more comprehensive understanding of the way policy, rebates and enticements can be introduced to produce a more energy conscious and more energy efficient homeowner. Life Cycle Energy Analysis allows the homeowner to understand the whole of life impact of their choices with respect to energy and is crucial to being able to better predict home energy consumption and better improve energy choices for new homes, as well as retrofitting existing homes. Trends in Australia suggest comprehensive research into the social influences of homeowners and their motivations and understanding of energy retrofit.
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Future Research Life Cycle Energy Analysis is a comprehensive tool in understanding a whole of life scenario in residential dwellings in Australia. It allows homeowners the ability to assess the long-term and short-term energy benefits of any retrofitting scenario. Further studies into how social variables affect the understanding and decision making of homeowners is necessary in order to fully understand the energy needs in Australia’s existing housing stock. A thorough knowledge of Australia’s average dwelling, average occupancy and social attitudes will critically influence energy outcomes in all aspects of the residential sector, and is vital in ensuring our energy demand
References Australia/New Zealand Standard, 1998, Environmental management - Life Cycle Assessment - Principles and framework, ISO 14040:1998, accessed 28 February 2012, Australian Building Codes Board 2011, accessed 28 April 2012. http://www.abcb.gov.au/ Department of the Environment 2008, Energy Use in the Australian Residential Sector 19862020, Cat no. 978-1-921298-14-1, Department of the Environment, Water, Heritage and the Arts, Canberra. Dong, Kennedy, et al. 2005, "Comparing life cycle implications of building retrofit and replacement options", Canadian Journal of Civil Engineering, Vol.32, 6, pp. 1051-1063. Falcone 2011, Energy Retrofit of Residential Buildings in a Hot Climate, Doctoral School in Structural Engineering Salerno, Department of Civil Engineering: University of, Ponte don Melillo. Fay, Treloar, et al. 2000, "Life-cycle energy analysis of buildings; A case study", Building Research and Information, Vol.28, 31-31. Hogan 2011, "A Design Approach to Achieve the Passive House Standard in a Home", MArch, Department of Architecture, University of Oregon, (UOO). Morrissey and Horne 2011, "Life cycle cost implications of energy efficiency measures in new residential buildings", Energy and Buildings, Vol.43, 915-924. Ramesh, Prakash, et al. 2010, "Life cycle energy analysis of buildings: An overview", Energy and Buildings, Vol.42, 1592-1600. Reardon, Milne, et al. 2010, Your Home Technical Manual, Fourth Edition, Department of Climate Change and Energy Efficiency, Efficiency, Department of Climate Change and Energy, Canberra. Yohanis and Norton 2002, "Life-cycle operational and embodied energy for a generic single storey office building in the UK", Energy, Vol.27, 77-92.
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A Policy Framework for Zero Carbon Buildings in Australia Phil Harrington1 This paper reviews the current dilemmas confronting building efficiency policy in Australia, outlining the factors that are inhibiting progress towards the necessary and achievable goal of zero carbon, or zero net energy, buildings. It notes that policy settings are deeply conflicted, with different arms of government working towards very different goals – with net result being a stalemate. Policy makers are also seemingly unsure how to respond to the paradigm shift that has hit them from left field, with the new-found cost-effectiveness of photovoltaic (PV) technologies in particular, and other embedded electricity generation technologies to a lesser degree. Positive initiatives include tentative steps towards mandatory disclosure of building energy performance. Also, despite their many critics, building ratings schemes are leveraging significant improvement in building energy performance through both voluntary and mandatory measures. However, despite evidence that minimum performance standards for buildings are too low – dramatically so for commercial buildings – and that zero net energy is already a cost effective performance target for some building classes, ineffective governance arrangements for buildings policy nationally and a significant flaw in the Carbon Pricing Mechanism are holding back movement towards this goal. This paper proposes a ’10-point plan’ to get Australian buildings policy back on track.
1. Background and Context 1.1 Energy and Emissions Profile of Buildings in Australia Buildings – or perhaps more accurately, human activity in constructing and using buildings – are a major source of energy consumption and greenhouse gas emissions in Australia, and also around the world. The International Energy Agency attributes around one third of global final energy consumption, and a similar share of global greenhouse gas emissions, to buildings (IEA 2011). In Australia, buildings’ share of final energy consumption is much lower, due to the distribution of energy consumption being skewed towards minerals processing in particular. Also, official statistics in Australia are organised by economic sector and allow only approximations to be made with respect to buildings as an end-use for energy. On this basis, building use accounts for around 18.5% of final energy consumption in Australia, while the construction sector accounts for less than an additional 1% (RET 2011). The share of greenhouse gas emissions in Australia attributed to buildings is higher, at around 23% (pitt&sherry 2010), due to the predominance of electricity as the final energy carrier in buildings together with the very high greenhouse intensity of electricity generation in Australia, where brown and black coal dominate as the primary fuels. Further, the same
1
Principal Consultant, Pitt&Sherry, GPO Box 94, Hobart TAS 7000
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source cites ABARE data showing that total energy use in residential buildings more than doubled between 1973 and 2004, while total energy use in commercial buildings tripled over the same period. There are excellent reasons to seek to reduce, and perhaps eventually eliminate, this source of energy use and greenhouse gas emissions.
1.2 The Climate Change Driver First, and some six years ago now, the Intergovernmental Panel on Climate Change declared that “Warming of the climate system is unequivocal…” and that “Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic GHG concentrations” (IPCC 2007). Since then, and based on more recent scientific observations, research and modelling, some climate scientists are concerned that “BAU scenarios result in global warming of the order of 3 – 6oC”; that “…goals of limiting human-made warming to 2oC and CO2 to 450 ppm are prescriptions for disaster”; and that “Rapid reduction of fossil fuel emissions is required for humanity to succeed in preserving a planet resembling the one on which civilisation developed.” (J.E. Hansen and M. Sato, 2012).
1.3 The Energy Price Driver Second, around the world, but very notably in Australia, energy prices have been rising strongly and are expected to continue to do so in future, albeit with some moderation expected in the short to medium term due to continuing weak global economic conditions and other factors. Electricity prices in Australia have increased most impressively in recent years, with nominal retail prices rising by 72.4 per cent in the five years to June 2012, equivalent to an increase of over 50% in real (inflation-adjusted) terms (Productivity Commission, 2012). Natural gas prices in Australia, retail or wholesale, are much less transparent than electricity prices and also show distinct variation by State. However, there is evidence that wholesale gas prices in Western Australia have more than doubled since 2009-10, while average retail gas prices have increased by over 40% in real terms since 1991 (AER, 2011). As a result the ‘business case’ for saving energy in buildings in Australia has never been stronger.
1.4 Efficiency and Abatement Potential of Buildings Third, it is extremely well established that the technical and economic potential for saving energy in buildings is very large. A recent review of Australian and international literature in this area showed that international literature suggests that up to 70% of energy use in new buildings could be avoided in most OECD countries with no or very low incremental costs, while Australian literature is more conservative, with savings potentials clustering around 30% (pitt&sherry 2010). It should be noted that this literature focuses on energy efficiency and does not consider the potential for embedded generation from low or zero carbon sources to cost-effectively reduce the demand for purchased or networked energy in buildings.
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A more recent reference examines more closely the potential for cost effective energy savings in Australian buildings, based on social benefit cost analysis and detailed, bottom up modelling of a wide range of building types, over the period to 2020 under a number of energy price, carbon price and other scenarios. This work finds that for new residential buildings, without PV, and in a reference scenario for energy and carbon prices, only some 16% of space conditioning energy consumption could be cost effectively saved by 2020, relative to the 2010 standard requirements, on average across Australia (pitt&sherry 2012). This value was significantly higher in some States where electricity prices are relatively high, for example, 36% savings were found to be cost effective in Perth, Western Australia. However, these results do not include the value of avoided energy network infrastructure savings – a key factor that is discussed further below. More importantly again, when PV was allowed as part of the building solution, the cost-effective level of savings rose to 100%. That is, zero net energy houses are shown to be cost-effective in Australia, indeed by 2015 or earlier in all States except those with the lowest electricity prices. For commercial buildings, the ‘reference scenario’ level of cost effective savings (without PV), relative to 2010, is much higher than for residential buildings – 58% on average by 2015 and 68% on average by 2020. Again significant regional variations were in evidence, with the highest result being 80% in Darwin, Northern Territory (where electricity prices and ambient temperatures are high and (cheaper) natural gas is largely unavailable). For many commercial building types, the availability of PV or other embedded generation options does not make proportionately as much difference to the cost effectively level of energy performance as it does for residential buildings. With respect to PV, this is due to the often restricted façade area with appropriate solar access, but also higher energy densities, of commercial when compared to residential buildings. However, the same study notes that for supermarkets, zero net energy is marginally cost effective. Supermarkets in Australia are cooling dominated, large and low-aspect-ratio ‘box’ form buildings, with limited glazing and significant internal heat loads from lighting and refrigeration adding to their already substantial cooling task. The study suggests that there is an expectation of significant improvements in the efficiency of lighting, refrigeration and space cooling energy technologies over the period to 2020. Further, these buildings almost invariably use (high cost, high carbon) electricity for 100% of their energy needs, and they also generally have excellent solar access for PV. It is the combination of all these factors that generates the result of cost effectiveness at a zero net energy performance level.
1.5 The Network Cost Driver It was noted above that real electricity prices in Australia have risen by over 50% in just five years. While more than one factor has contributed to this outcome the Productivity Commission, amongst many other analysts, has noted that “Spiralling network costs are the main contributor to these increases, partly driven by inefficiencies in the industry and flaws in the regulatory environment.” (Productivity Commission, 2012, p. 2). While a full description of this issue is beyond the scope of the present paper, the fundamentals are that some 70% of the peak electrical load in Australia is attributable to
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buildings and around two-thirds to residential buildings alone. Most climate zones in Australia experience wide diurnal and seasonal variations in temperature. Air conditioned commercial buildings are the norm, while residential air conditioning has grown strongly over the last decade or more. The percentage of households with air conditioners increased from 20% in 1970 to around 75% in 2011 (Productivity Commission, 2012b), and this is generally cited as the proximate cause of rising peak system loads in Australia. The cooling demand of buildings (and, to a lesser degree, heating demand of buildings in winter), is therefore by far and away the dominant driver of rising peak load, and rising peak load is far and away the dominant driver of rising electricity prices in Australia. The Productivity Commission has noted that “capacity that caters for less than 40 hours a year of electricity consumption (or under one per cent of time) accounts for around 25 per cent of retail electricity bills” (Productivity Commission 2012b, p. 301). This leads not only to higher than necessary electricity prices, it also creates poor productivity for investment in network assets and electricity generation. It should be understood as a misallocation of economic resources driven by poor market design. However, we could express this conundrum another way. We could say – on the above evidence – that the demonstrably sub-optimal thermal performance of buildings in Australia, the non-realisation of the very large, demonstrated cost-effective potential for efficiency improvement in buildings, is the largest single cause of rapid growth in electricity prices in Australia, and also of rising energy demand and associated greenhouse gas emissions associated with buildings. Clearly, other factors are also at work. These will include rising incomes, larger houses (and commercial building space per capita), longer operating hours for commercial buildings, rising ‘plug load’ (notably electronic equipment) and standby power. An investigation of their role falls outside the scope of this paper. Instead, this paper focuses on why – given the remarkably strong prima facie case for strengthening building energy efficiency policy in Australia – there appears to be little or no appetite for policy reform? Despite the opportunity to cost-effectively reduce energy consumption and costs for businesses and households alike, and despite the opportunity to realise cost-effective greenhouse gas emissions savings, in some cases all the way down to zero net energy or carbon – why is it that there seems to be little appetite or momentum for policy development?
2. Building Energy Efficiency Policy in Australia 2.1 A Potted History It is not within the scope of this paper to provide a comprehensive history of buildings efficiency policy in Australia. Suffice to note that Australia embraced energy performance regulation of buildings late, at least at the national level. Some States, like Victoria and the Australian Capital Territory (ACT), had introduced some prescriptive requirements (such as insulation requirements) into their state Building Codes in the 1990s. The ACT introduced mandatory disclosure of residential building energy performance in 1999…something that has still not been implemented across Australia despite being agreed by the Council of Australian Governments in 2009 (NSEE 2009).
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Building energy performance measures were first introduced for some residential buildings (Classes 1 and 10) in 2003 and for others (Classes 2 – 4) in 2005. Class 1 building requirements were lifted to 5-star (see below) at that time and to 6-star in the 2010 version of the Building Code of Australia. For commercial buildings, energy performance requirements were first introduced in 2006 and then lifted in 2010. In addition the scope of Code requirements has been broadened; for example, requirements for lighting energy density, hot water greenhouse gas intensity and pool pump energy usage were included for residential buildings. There is some evidence that the stringency of both past and current requirements is modest, particularly for commercial buildings. For example, it was retrospectively calculated that the required social benefit cost ratio set as the ‘hurdle rate’ for commercial buildings in 2006 was a remarkable 4.9:1 (CIE 2009). This clearly indicates that much more ‘benefit’ (energy savings) could have been realised whilst remaining cost effective. More recently, the benefit cost analysis of future Code stringency (pitt&sherry 2012) indicated high benefit cost ratios for commercial buildings even in the very short term, suggesting that BCA2010 performance requirements were once again very conservative. Also, it should be noted that individual states were then (and are today) given considerable latitude in both the timing of the implementation in their states of nationally-agreed performance measures in the Building Code of Australia, and secondly in making statebased ‘variations’ to these provisions, notionally to accommodate local factors. COAG first agreed to 6-star housing in 2008, for example, but this performance requirement will not be adopted in Tasmania until 2013, fully five years later. Building ratings schemes deserve a brief mention in this context. The benchmark rating system for residential buildings is NatHERS (the National House Energy Rating System), developed and administered jointly by Federal and State/Territory governments since at least 1995, although other ratings tools have been developed (FirstRate, BERS). For residential buildings, energy performance requirements in the Building Code of Australia (or, more strictly, space conditioning energy consumption) is determined by reference to NatHERS star ratings levels, although other solutions (including a ‘Deemed to Satisfy’ or prescriptive route) are also accepted. For commercial buildings, the NABERS (National Building Energy Rating System) is the most widely used energy rating tool, although the Green Star sustainability rating is also popular for premium buildings (and in any case draws on NABERS for its energy ratings component). NABERS underpins the mandatory disclosure regime for commercial buildings, known as Commercial Building Disclosure, but may not be used to demonstrate compliance with the energy performance requirements in the Building Code of Australia (Section J). Instead the Code uses a ‘reference building’ simulation approach. Despite having many critics, it is clear that these ratings tools have a) enabled firstly a small market for building energy efficiency to be established on a voluntary basis; b) enabled a much larger market to evolve through mandatory application (BCA, and now Commercial Building Disclosure); and c) continue to support ‘beyond minimum compliance’ and best
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practice on a voluntary basis, by providing a credible and reliable ‘metric’ for the measurement and demonstration of building energy performance. In 2009 the Council of Australian Governments (COAG) endorsed a National Strategy on Energy Efficiency. This Strategy included, inter alia, the development of an ‘integrated framework for national building energy standard-setting, assessment and ratings’ (NSEE 2009). The Framework has the laudable goal “...to drive significant improvement in Australia's building stock through establishing a pathway for future increases in minimum building standards to 2020, and improving the approach to assessing and rating buildings” (DCCEE 2012). It is intended that the the Framework will: •
set increasingly stringent minimum building standards over time for new buildings and renovations
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cover all types of residential and commercial buildings
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apply to new and existing buildings
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cover the building envelope including roof, walls, doors and windows, as well as the energy efficiency of key building equipment and services
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aim to harmonise assessment and rating tools for existing and new buildings
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include common measurement and reporting methodologies to help in setting building standards and assessing building performance
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encourage innovation in meeting defined performance standards
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continue to communicate building performance using star ratings, and
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facilitate effective monitoring and compliance.
The process has proceeded from a policy commitment in 2009 to a Discussion Paper in 2010 to a Draft Framework by late 2012. Stakeholder consultations were held in early 2012. It is unclear when or whether a Final Framework will appear and also when or whether the above goals will be achieved. The barriers are discussed in the following section.
2.2 The Present Malaise At least five factors appear to working against the establishment of a fit-for-purpose building energy efficiency/carbon framework that would take Australia towards the goal of zero carbon buildings within a defined timeframe. These may be summarised as: 1. A lack of political will, which in turn reflects a) Australia’s weak climate change target, and b) a view that Australia’s carbon pricing mechanism makes most other policy measures – and certainly building energy performance requirements – redundant; 2. A lack of a credible national energy efficiency policy, and the absence of energy efficiency targets;
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3. A lack of co-operation between the Commonwealth and major States/Territories, augmented by unclear accountability for buildings policy and regulation between jurisdictions and even agencies within jurisdictions; 4. An apparent unwillingness to deal with the ‘paradigm shift’ that is being worked by low-cost PV, which in turn reflects short-comings in wider energy policy and regulation; 5. At a more technical level, a lack of appropriate guidelines, research and data to underpin realistic benefit cost analyses and regulatory impact assessments – the net effect of which is generally to overstate the costs and understate the benefits of building energy performance regulation. Each of these barriers is discussed briefly below.
2.3 Climate Policy and the Carbon Pricing Mechanism One might suppose that the potential for large and highly cost-effective greenhouse gas abatement benefits, as well as significant economic and social benefits, would be welcomed and embraced by the designers of climate policy in Australia, and responded to with much strengthened and forward-looking policy settings. The reality is somewhat different. The Australian Government views its carbon pricing mechanism (CPM) as its primary policy instrument to achieve its climate policy goals. It is actively discouraging new policy measures and indeed seeking to prune out as many existing policy measures as possible. It justifies this view on the grounds that pricing carbon represents a ‘least cost’ approach to reducing emissions. Setting to one side the research that conclusively demonstrates that this is not (necessarily) so, the CPM presents two major threats to the development of a policy framework that would enable the realisation of a goal of cost-effective, zeroenergy/zero-carbon buildings in Australia. First, the carbon saving effect of what are now referred to (disparagingly) as ‘complementary measures’ (that is, any measure that is not the CPM) is not ‘additional’ to the cap mechanism under the CPM. Under a cap-and-trade scheme, it is the level of the cap that determines the volume of allowed emissions, in every year, from the sectors of the economy ‘covered’ by the scheme. The Clean Energy Act 2011 prescribes a number of factors that must be taken into account when recommending to the Minister the level of future caps (the decision itself, however, is left to the Minister’s discretion). These factors fail to include the abatement effect of existing (or future) ‘complementary measures’, even if a discretion exists for the Climate Change Authority (that advises government on the caps) to consider ‘other relevant matters’. While this may seem a technical point, it means that the very substantial abatement effect of building energy efficiency measures – and indeed of many other measures besides – counts for precisely nothing once the cap mechanism is in place (from 2015). Therefore, building energy policy – as with most other ‘complementary measures – is vulnerable to the criticism
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that ‘it won’t add one gram of abatement to the national effort, so why don’t we get rid of it?’. This view has been starkly put to government, and indeed to COAG, by the Productivity Commission (Productivity Commission, 2012c). Those who put this view fail to acknowledge that this ‘additionality’ problem is entirely a creation of one section of one Act of Parliament; ie, a policy failure that could readily be corrected. The fact that this is neither acknowledged, nor less acted upon (by amending the Act), may be traced back to the afore-mentioned view that carbon pricing must be the primary climate policy instrument. This view is pursued in Australia with a degree of zeal that suggests that it is based on something other than rational analysis. However, the second threat that climate policy poses to building energy performance regulation is complacency. Australia’s official climate abatement target is to achieve a 5% reduction in 2000 emissions by 2020. Due to the slow down in the global and large parts of the domestic economy; a particular slowdown in forest harvesting due to both global and local economic factors; changes in the national energy market that largely preceded carbon pricing (and many of which are attributable to the same energy efficiency and renewable energy policy measures that are now under threat on ‘complementarity’ and ‘additionality’ grounds), and – to be fair – to some additional abatement effect from the CPM itself, there is now a view that Australia may achieve its target without further policy development...including building energy efficiency policy. Given the climate science reviewed very briefly above, it is at least a tenable view that we have no grounds for complacency. Australia is amongst the highest per-capita greenhouse polluters in the world. The Australian Treasury’s analysis of the carbon pricing mechanism clear states an expectation that by 2050 (nearly 4 decades into the future), actual emissions in Australia will be just 2% below their level in 2000, while the difference between this any political goal (which has been set at 80% below 2000 by 2050) will be made up by purchasing offsets (Treasury, 2011). Our plan to rely on carbon trading, and to import ‘certified abatement’ rather than reduce emissions domestically through genuine structural reform and best practices, is of questionable ethical integrity, and may not even pass the purely mercantile test of ‘least cost’.
2.4 Energy Efficiency Policy In 2009 the Australian Government established an Energy Efficiency Task Force to report directly to the Prime Minister on strategic energy efficiency policy. The Task Force duly reported in July 2010, making 44 detailed recommendations, starting with the setting of a national energy efficiency target or goal. To date, only two of the 44 recommendations have been responded to by government. First, it rejected out of hand the concept of a national energy efficiency goal or target. The justification for this may be found in the above discussion on climate policy and the role of the CPM. Second, it agreed to ‘consider’ a national energy savings initiative (conceived of as a ‘white certificates’ scheme). At the time of writing, the consideration process goes on, with only a ‘Progress Report’ having been publically released. The balance of 42 detailed recommendations to the Prime Minister remain unresponded to, either in the positive or in the negative.
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2.5 Policy Governance Building regulation has traditionally been viewed as a Constitutional responsibility of the States and Territories. Australia’s Constitution – unlike many – assigns an ‘exclusive’ list of functions to the Commonwealth, while all functions remain with the States…at least in theory. Building regulation apparently did not rate highly in the minds of our ‘founding fathers’, and therefore does not rate a mention in our Constitution. On this basis, it belongs to the States. However, the Commonwealth is responsible for the regulation of corporations, and also for implementing ratified international treaties (such as the UN Framework Convention on Climate Change and Kyoto Protocol, for example). The Commonwealth has also most of the taxation powers in Australia and therefore captures the vast majority of government spending power, even if much of the revenue is ‘recycled’ to the states under various mechanisms. As a result of these factors, and others besides, governance of buildings policy generally in Australia is contested and unclear. At the time of writing, political tensions and budgetary pressures are also adding to a policy ‘stand-off’ between jurisdictions, with building energy efficiency policy apparently one of many casualties. It is hard to judge whether, given the two factors noted previously, whether this third factor is material or not. We can, however, be sure that it is not helping.
2.6 The PV Paradigm Shift PV technology – originally developed by NASA for use on satellites – has until very recently suffered from high capital costs. However, since around 2007, the price of panels has fallen by up to 90% (pitt&sherry 2012). This is one of the key factors – along with rising electricity prices – that is making PV on buildings increasingly cost effective. One might again be forgiven for thinking that this development would be a cause for much rejoicing and celebration amongst policy makers, however no such levity is evident. PV is a ‘disruptive technology’ – one that breaks the current electricity market paradigm – itself based on remote, large-scale and generally fossil-fuel powered generation, owned by large (and, in the past, state-owned) corporations, transmitted and distributed by either stateowned or private regulated monopolies, and sold by retailers to passive consumers. The flow of energy is one way; the flow of money, the other. Energy efficiency in this system is remarkably low, while greenhouse gas emissions are very high. PV, and other low-carbon embedded generation technologies, turns this paradigm on its head. The generation technology is low- or zero-carbon; it is owned by consumers; it is distributed not centralised; the flow of energy and money is two-way between consumers and others in the power system; and large corporations – state-owned or otherwise – have little to do…other than cope with more complex and dynamic power flows (another paper would be required to describe this in detail). Interestingly the extremely high level of electricity prices that have, as noted above, been generated in Australia, as a result of the first paradigm, is also driving consumers with increasing rapidity towards the second. A ‘market response’ indeed. Thus, an industry that has evolved to ‘clip the ticket on the way
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through’, as power flowed downhill in the first paradigm, suddenly can feel its business model being undermined. Not surprisingly, the industry is pushing back, as are the governments that design the energy market, regulate the market players and often own the businesses that participate in the market. The result that PV may make zero energy or zero carbon buildings cost effective in Australia is troubling for policy makers…not in buildings policy, and not for those interested in a clean, low carbon and sustainable future, but in energy policy and in our Treasuries.
2.7 Analytical Constraints While a lesser and more technical issue, the lack of adequate data, statistics and funding for the development of the same, does hold back the creation of compelling ‘business cases’ for buildings policy inter alia. Further the Orwellian-named Office of Best Practice Regulation in Australia – which essentially sets the rules for quantitative and impact assessment of regulation in Australia – insists on high hurdle rates (at least 7% real) and does not prescribe that learning effects, technological change and other factors (that might improve the business case for regulation) be included in the analysis. Of course, these may be included…provided they are specified in the briefs let by the policy agencies (which is rare), and provided research has been done to enable these factors to be quantified (which is even more rare).
3. Conclusion – A 10 Point Plan What would it take to overcome the barriers noted in this paper, and instead to realise the opportunities presented by cost-effective, zero energy/zero carbon buildings in Australia? The answers are suggested in the above points. For economy, they are summarised in point form: 1. Australian governments should publically acknowledge that building energy performance in Australia is poor, and that this is a major drive of a) greenhouse gas emissions, b) costly and unnecessary energy consumption, c) energy system cost impacts, and d) therefore, a major driver of rising electricity prices in Australia; 2. Australian governments should publically acknowledge that there is very large potential for improving the thermal and energy performance of buildings, and that creating policy settings to capture this potential would be a highly effective and cost effective strategy for responding to point 1) above. Alternative solutions to these issues should be benchmarked against building policy and the least cost options chosen…if indeed we believe in least-cost and rational public policy; 3. Australian governments must set high, but evidence-based, standards and goals, not the low ones that have applied, and continue to apply, today. This includes with respect to climate policy, energy efficiency policy and buildings energy efficiency policy more narrowly.
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4. The Clean Energy Act 2011 must be amended to remove the policy failure that results in the ‘non-additionality’ of building energy efficiency policy and all other nonCPM policies and measures; the pejorative term ‘complementary measures’ should be consigned to the dustbin of history. 5. The governments’ laudable goal of creating an integrated framework for regulation, assessment and rating of building energy performance should be put into effect as soon as possible. To the framework I would add an effective mechanism to ensure compliance with existing and future buildings regulation. 6. The Australian Government should respond without further delay, in detail and positively to the 44 recommendations of the Prime Minister’s Task Force on Energy Efficiency, including by setting an ambitious national energy efficiency (not intensity) target, with a detailed, measure-by-measure, year-by-year plan for its achievement. 7. Governance arrangements for the building industry must finally and definitively be settled. The flood of powers from the states and territories to the Commonwealth suggests the direction in which this might be resolved. However, that outcome should be contingent upon the commitment of the Australian Government to put in place – and keep in place – and to fund – a credible buildings policy in Australia. 8. Governments in Australia, and their agencies responsible for energy policy, must come to grips with the PV/distributed energy paradigm shift. To date, the key response has been to worsen economic conditions for PV, in the hope that it will go away. It won’t. 9. Governments in Australia, and primarily the Australian Government, must fund the creation and maintenance of adequate, fit for purpose and publically-accessible data sets, and also the conduct of public interest research on public policy matters, including building energy efficiency, on an adequate, secure, long-term and independent basis. 10. Above all, Governments in Australia should offer genuine leadership on climate policy in particular, ensuring inter alia that targets are based in science and not politics; that policy is based in genuine and rational analysis, sound data and not ideology; and that buildings policy in Australia receives the enhanced focus and support that it deserves.
References AER (2011) State of the Energy Market 2011, Australian Energy Regulator, Australian Government, 2011. CIE (2009) Consultation Regulation Impact Statement – Proposal to Revise the Energy Efficiency Requirements in the Building Code of Australia for Commercial Buildings –
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Classes 3 and 5 to 9, prepared by the Centre for International Economic and published by the Australian Building Codes Board, 2009. IEA (2011) Technology Roadmap: Equipment. OECD/IEA, 2011.
Energy-efficient Buildings:
IPCC (2007) Climate Change 2007: Synthesis Report: Intergovernmental Panel on Climate Change, 2007.
Heating and Cooling
Summary for Policymakers.
J.E.Hansen and M.Sato (2012). Paleoclimate Implications for Human-Made Climate Change, James E. Hansen and Makiko Sato, NASA Goddard Institute for Space Studies and Columbia University Earth Institute, New York, 2012. pitt&sherry (2010) The Pathway to 2020 for Low-Energy, Low-Carbon Buildings in Australia: Indicative Stringency Study, published by the Department of Climate Change and Energy Efficiency, Australian Government, 2010. Productivity Commission (2012) Electricity Network Regulatory Frameworks – Draft Report Volume 1, Productivity Commission, Australian Government, October 2012. Productivity Commission (2012b) Electricity Network Regulatory Frameworks – Draft Report Volume 2, Productivity Commission, Australian Government, October 2012. Productivity Commission (2012c) COAG’s Regulatory and Competition Reform Agenda: a high level assessment of the gains, Productivity Commission Research Paper, Australisan Government, June 2012. NSEE (2009) National Strategy on Energy Efficiency, Council of Australian Governments, 2009. RET (2011) Energy in Australia 2011. Department of Resources, Energy and Tourism, Australian Government, 2011.
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Towards a New Advanced Industry for an Energy Efficient Built Environment Luc Bourdeau1, Stefano Carosio2 Abstract The key objective of the Energy Efficient Buildings Association (E2BA), representing a large set of stakeholders of the construction sector and associated technology sectors, is to promote the creation of an active industry for the production, supply/distribution of advanced systems, solutions and added value services with a view to satisfy the needs on energy efficiency for the built environment. The Association is engaged since 2009 in a Public-Private Partnership on Energy-efficient Buildings (PPP EeB) with the European Commission (EC) to develop and deploy a full Research, Development and Innovation (RDI) program at EU level. As a matter of fact, buildings provide a large untapped cost effective potential for energy savings, but in order to speed up the deployment of key technologies at least cost, it is crucial to increase innovation in the fields of energy efficient construction processes, products and services. The paper includes a brief presentation of the main results of the tenths of collaborative trans-national RDI projects launched in the framework of this PPP. Some of these results are already available and disseminated by the projects; some of them are still under development. It is also dedicated to the presentation of the new Roadmap recently prepared by the Association in cooperation with the EC, containing the major RDI challenges faced by the sector by 2020 to meet the EU decarbonization goals. Keywords: energy efficiency, buildings, districts, smart cities
1. Introduction Worth at least 1.3 trillion Euros of yearly turnover in 2010, the European building sector and its extended value chain (material and equipment manufacturers, construction and service companies) is on the critical path to decarbonize the European economy by 2050. It must enable reducing its CO2 emissions by 90% and its energy consumption by as much as 50%. This is a unique opportunity for sustainable business growth provided that products (new or refurbished buildings) and related services are affordable and of durable quality, in line with several past or future European Directives. Yet, together with the 2050 deadlines, such Directives are putting more constraints onto a sector which is directly impacted by the on-
1
Secretary General; Energy Efficient Building Association (E2BA); rue d’Arlon 63-67, B-1040 Brussels;
[email protected]. 2 Vice-president Innovation, D’Appolonia, Rina Group, Genova;
[email protected].
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going financial and economic crisis (less purchasing power, but also potentially increasing building costs due to more stringent requirements to meet building energy performances). The time frame left to develop innovative technology and business models in line with the 2050 ambitions is narrowing down to less than 10 years.
2. The running Public Private Partnership on Energy-efficient Buildings (PPP EeB) The running PPP EeB was launched as part of the economic recovery plan in 2008. The PPP EeB uses existing mechanisms of the Framework Programme of the European Commission (EC) whilst providing a mid-term approach to R&D activities. It brings together various Directorates Generals (DGs): DG Research and Innovation - Nano, Materials & Processes (NMP) and Environment (ENV) priorities -, DG Energy, and DG Communications Networks, Content and Technology, in close dialogue with industry. In this framework, a roadmap was built on the following pillars, namely: 1) systemic approach; 2) exploitation of the potential at district level; 3) geo-clusters, conceived as virtual trans-national areas/markets where strong similarities are found, for instance, in terms of climate, culture and behaviour, construction typologies, economy and energy/resources price policies, Gross Domestic Product, but also types of technological solutions (because of local demand-supply aspects) or building materials applied etc. These pillars are definitely brought forward in a new Research and Innovation Roadmap (to be published in 2013) which indeed is strongly based on the long term programme defined by the PPP EeB (2010) around a “wave action”. In this “wave action” plan, continuous, ongoing research feeds successive waves of projects as shown in Figure 1. The knowledge gained in the first “wave” feeds in the second at the design stage, realising a continuous implementation process.
Figure 1: Wave action along the roadmap (D&B: Design&Building; O: Operation)
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As a result of this “wave action”, industry expects to reach impact following a stepped approach, namely: •
Step 1: reducing the energy use of buildings and its negative impacts on environment through integration of existing technologies (main focus of the current PPP EeB);
•
Step 2: buildings cover their own energy needs;
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Step 3: transformation of buildings into energy providers, preferably at district level.
The long term programme set by industry tackles also the development of those enabling knowledge and technologies which are instrumental to achieve these targets, launching the required more fundamental and applied research actions. This long term approach has mobilised heavily industry with over 50% participation in calls and Small and Medium size Enterprises (SME) involvement beyond 30%, figures which are well above business as usual in collaborative research projects under the EC framework programme. Reviews by E2BA (2011, 2012) of the different running projects have highlighted some of the innovations under development, such as: • • • • • • • • • • • • • • • •
Nanotechnology coatings Integrated air quality sensors Tools to improve indoor environment Operational guidance for performing Life Cycle Assessment (LCA) studies Sustainable, innovative and energy-efficient concrete High performance bio-composites for buildings Component and systems for buildings, such as multi-functional façade panels Components and systems for districts, such as energy storage solutions Standardized building and user friendly models Energy control hardware Building Energy Management Systems (BEMS) Heating Ventilation and Air Conditioning (HVAC) control systems Energy performance simulation Virtual building models Integration of multifunctional energy modules Business models.
3. Overall vision till 2030 and strategic objectives 3.1 Vision 2030 Based on the achievements so far, the E2BA ambition is to drive the creation of an innovative high-tech energy efficiency industry extending the scope of the running PPP EeB beyond 2013. Connecting construction industry to other built environment system suppliers will be the decisive step for Europe to reach its economic, social and environmental goals, contributing to the objectives of the Innovation Union. By creating and fostering this
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paradigm shift, EU companies will become competitive on a global level in the design, construction and operation of the built environment while sustaining local economies across EU-27 through job creation and skills enhancement, driven by the vast majority of SMEs active in the value chain. In line with ambitious 2050 targets, it is expected that already in 2030 the entire value chain will produce advanced systems, solutions and high value services for intelligent and sustainable buildings and districts. The long term strategic objectives defined by E2BA (2012) include: •
Most buildings and districts become energy neutral, and have zero CO2 emission. A significant number of buildings would then be energy positive, thus becoming real power plants, integrating renewable energy sources, clean distributed generation technologies and smart grids at district level.
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Industry will employ highly skilled individuals capable of efficiently, safely and quickly carrying through construction processes. This means an extended value chain and collaborative “assembly” line delivering adaptive and multifunctional energy and resource efficient buildings and districts solutions.
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Unemployment will be kept low as skilled local jobs will be created through an effective and dynamic matching of demand and supply. Public Private Partnerships will indeed cover the entire innovation chain, fostering performance based contracting and innovation friendly procurement practices. This will be achieved with sustainable financial incentives schemes on the demand side. On the supply side, systemic technical solutions optimised at European scale will be integrated locally.
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Urban planning and smart cities implementation leverage on these novel solutions at building and district scale, creating the basis for intelligent connections between buildings and districts and all urban resources.
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Such globally competitive energy efficiency industry will be able to deliver new business opportunities, jobs and solutions. In terms of environmental impacts, greenhouse gas emissions will be reduced to 80-95% below 1990 levels, as required by the Energy Roadmap 2050 (COM(2011) 885/2). In addition, the use of renewable energy and efficiency technologies is extended as required by the Strategic Energy Technology Plan, the Energy Efficiency Plan and the recast of the Energy Performance of Buildings Directive (EPBD).
Indeed in Europe, each Member State with its own building stock is faced with a combination of four implementation options to comply with the challenges ahead, inevitably mixing rehabilitations and construction of new buildings: •
Option 1: increase significantly the rate of high performance, deep rehabilitation of commercial and residential buildings, while lowering the costs of rehabilitation.
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Option 2: increase the overall depth of rehabilitation by favoring district rehabilitation in priority.
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Option 3: valorise energy production and use within new districts to make these districts “energy positive”.
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Option 4: scrap all poorly insulated buildings and replace them by high performance buildings (energy neutral and, when possible, energy positive).
Member States have a reduced set of optimization parameters to address properly these options: •
the spatial scale chosen for energy demand optimization (single building versus district); the district dimension provides new energy optimization possibilities, for instance through the connection to existing grids (electricity, heat and cooling networks), via the design and operation of a set of buildings as components of an integrated energy system, which can in turn contribute to improved peak load management.
•
the rate of new constructions versus the rate of refurbishment which in turn is conditioned by: -
the depth of refurbishment versus the new building energy performance level (set by law)
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the split between technology-based (energy demand) and behaviour-based (energy use) solutions, whatever the project under scrutiny.
Implementing pathways at the right pace to make innovation breakthroughs possible requires the building sector to go through a profound mutation before 2030 which shape a vision as described below: Vision 2030 By 2030, increased and faster collective research and innovation has allowed the European building sector to mutate into a mature, innovative and energy efficient enabling industry: •
delivering new or refurbished, user centric and affordable buildings/districts in line with EU2020 and national strategic objectives and commitments towards 2050;
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working according to quality standards that encompass the whole life cycle of any building, thus guaranteeing durable building performances;
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valuing not only energy performances but also aesthetics, acoustics, accessibility or comfort as purchase criteria for end users;
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committing to long term performance guaranteed contracts on the energy bills.
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In doing so, industry aims at introducing as most technology and market flexibility as possible for the benefits of policy makers and investors when facing the decarbonisation of the building sector. Any mix of the above four scenarios can then be addressed by the building industry in the next 40 years, industrial maturity being reached by 2030.
3.2 The critical role of refurbishment Tackling refurbishment of existing building is a top priority; it is expected that, by 2050, about half of the existing building stock in 2012 will be still operational. BPIE (2011) emphasized the critical role of refurbishment, when considering various pathways to achieve the 2050 building sector decarbonisation goals. The proposed pathways differ from one another by: •
the speed at which buildings are refurbished (the refurbishment rate),
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the level of energy or greenhouse gas emission savings that are achieved when refurbishing a building (the refurbishment depth).
The BPIE study developed five scenarios that may or may not achieve the 2050 target for the building sector: only two work well –the Deep Scenario and the Two-Stage Scenario. When comparing these two scenarios with the current situation, it can be seen that: •
both rate and depth of refurbishment must at least double and even triple, compared to the currently observed situation,
•
the depth of refurbishment must start increasing before 2020 to avoid the need for a twostage refurbishment process, which in turn would yield a higher share of zero energy buildings by 2050.
Nevertheless, the BPIE study has not addressed the impact of a third critical parameter: the district dimensions which could possibly relax either one of the above trajectory parameters and innovation, since allowing for cross building energy cooperation and/or smart energy generation and use within districts. At any rate, deep refurbishment will be required, meaning: •
breakthrough technological and economic performance improvements for the building envelope (reduce the demand);
•
proper downscaling/management of energy equipment (adjust to a lower demand without losing energy use efficiency);
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durable performance improvements (avoiding user’s misuses and/or building disorders).
Another relevant aspect not considered is this report is the associated investment to these scenarios. Research and innovation are clearly needed to reduce the huge additional investment required to reach the renovation targets in terms of energy efficiency, which are measured over 60 billion € additional investment per year. Finally, a last aspect which the
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paper does not include but may hinder innovative and energy efficient refurbishment is represented by the large number of micro and small enterprises involved in the refurbishment operations: it is well known the uptake of innovative technologies by SMEs is rather slow due to limited economical and knowledge resources.
4. Research and Innovation Strategy 4.1 Methodology The preparation of the EeB Roadmap has been driven by industry in the framework of the Ad-hoc Industrial Advisory Group set-up within the running PPP EeB. The private sector is represented by the European “Energy Efficient Buildings Association” (E2BA), as industrial interlocutor of the European Commission in the PPP EeB. The scope of the Roadmap was indeed to update the research and innovation priorities to align the industry long term plans with the content of the next EC RDI Framework Programme “Horizon 2020” proposal, where a clear research line on “Technologies for Energy efficient Buildings” has been proposed by the EC. In this framework an extensive review of running research and demonstration projects and major initiatives at EU scale such as the SET Plan (including the recent Roadmap on materials enabling low carbon energy technologies ), the Smart Cities European Innovation Partnership, the Intelligent Energy and Eco-innovation programmes under the CIP framework, the InnoEnergy Knowledge and Innovation Community (KIC) running under the European Institute for Innovation and Technology (EIT), the Lead Market initiative and recent Communication on “Sustainable Construction” by DG Enterprise as well as the Energy efficient roadmap and consultation on “Financial support for energy efficiency in buildings” by DG Energy, to name a few. Inputs and contributions from key stakeholders have been mobilised within the framework of the ICT4E2B Forum (www.ict4e2b.eu) and Building-Up (www.buildingup-e2b.eu) projects gathering experts from construction, energy as well as ICT domains, and relevant European Technology Platforms (i.e. European Steel Technology Platform (ESTEP), Forest-Based Sector Technology Platform (FTP), European Technology Platform for Sustainable Chemistry (SusChem), European Technology Platform for Advanced Engineering Materials and Technologies (EUMAT), European Technology Platform for the future of Textiles and Clothing). They have been complemented by inputs and feedbacks received within an open consultation launched in early July 2012 and closed on October 1st 2012. The innovation rationale proposed by industry is to extend the ambition of the running PPP EeB beyond 2013 in line with the 2030 vision to develop and to validate a set of innovative integrated to novel tools, technology and process components covering the whole value chain. They will then be integrated to meet future market conditions, thus: •
transforming barriers and regulatory constraints into innovation opportunities,
•
fostering the creation of innovative supply chains, that become more user centric to cope with the difficulty of implementing refurbishment strategies,
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•
reorganizing and stimulating innovative procurement of buildings and ordering of technology/services with the integration of new smart grids technologies for single buildings as well as for whole districts (new buildings and existing stock).
Today’s fragmented nature of the construction chain still gives little freedom for innovations that are indispensable to shape a more sustainable built environment. Yet, collaborative project management in the construction sector has become a prerequisite to develop a building stock that is technically and economically optimized: this goes against centuries of working habits. Moreover, the focus must be on creating value (not only in terms of economics, but also in terms of comfort, health, environment, etc.) for all the users involved. This requires new skills together with a major behavioural shift within the entire construction sector. Coalitions must be given birth, dedicated to collaboration between players from different disciplines to contribute to the realization of buildings with energy-ambitious goals. The whole value chain (see Figure 2) will be involved in this continuous optimization process which follows three major steps: •
Step 1: From design to commissioning of new or refurbished buildings, the optimization consists in picking amongst a portfolio of material and energy equipment solutions, the ones which meet both a cost of ownership target and minimal potential GHG emissions over the foreseen life cycle.
•
Step 2: During this life cycle, robust user-centric energy management systems ensure that the initial GHG emissions targets are continuously met thanks to adaptive energy management tools able to correct for or modify behaviours of users. Only natural ageing of technology can impact the initial energy performance at commissioning.
•
Step 3: The next refurbishment involves another optimisation approach where the investment for refurbishment can be recovered through further savings on the cost of ownership.
Figure 2: Representation of the segmentation of the value chain and road mapping process
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This optimisation approach requires that all the stakeholders perform according to quality rules where interfaces and responsibilities between any of them are transparently exchanged. The innovation process will be open to various technologies, materials or processes focussing on valuable improvements. Interaction with other research areas especially the integration of supply systems for renewable energy including storage systems will be mandatory. Indeed novel Information and Communication Technologies (ICT) as well as materials technologies will be key enablers throughout the whole value chain, from the design phase to the end of life. An overview of the enabling role of ICT is provided in Figure 3.
Figure 3: The pervasive role of ICT along the value chain
4.2 Main elements of the strategy It is at the design stage that more than 80% of the building performance is set both in terms of energy savings (generation when embedded in a zero energy district) and cost of ownership over the life cycle before refurbishment. Yet, the relative gap between the design value for energy performance and the commissioning measured result is still too large (and will probably widen when the more stringent building code standards for 2020 are in place). A new regional and urban planning of smart grids and cities promotes decisions at the design phase for better solutions. Thus, planning with a holistic approach for energy-efficient and sustainable buildings (new and refurbished) will be mandatory. Hereby, ICT technologies from true interoperability to decision support systems can be used.
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Load bearing structural parts of a building can be mechanically and thermally optimized with sophisticated tools: the focus must now be put on the embedded CO2 which comes from the materials (concrete, various brickwork, steel, wood …). This CO2 will become the most prominent part of GHG emissions as the share of energy neutral building grows. Alternative construction processes e.g. with significantly lower embodied energy will help to bind CO2. Hereby, renewable energies and sustainable cultivation plays a key role. The building envelope becomes the most critical part when it comes to energy efficient buildings: •
For new buildings, materials and energy equipment integration already allows reaching very low energy demand (e.g. based on a high heat resistance, high air tightness or integrated ventilation systems with connection to heat recovery systems). Yet, the investment costs have to be further reduced while taking care of several other design constraints (acoustics, fire, seismic, air quality, adaptation requirements for ageing population...). In the long run, active envelope could make buildings energy positive by, for instance, smartly managing solar fluxes onto the building.
•
For refurbishment, the diversity of architectures and climates in Europe requires a whole value chain innovation process where design, technology choice and construction are even more intertwined than for new buildings – special efforts are likely to be necessary for cultural heritage buildings. The integration of the district dimension can allocate refurbishment performance settings to reach very ambitious zero energy districts. Overall, refurbishment depths must go beyond 70% while valuing non energy related benefits to make the business models more attractive.
•
Prefabrication of envelope parts, multi-functionality and compact solutions presumably will significantly reduce costs and produce new markets.
The energy equipment must adapt to the new smart grids and to lower unit energy demands from more energy efficient buildings, which requires sizing down to-day portfolio while keeping energy efficiency at the highest level possible as well as unit investment cost down. Beyond existing technologies, breakthrough solutions can be expected from heating/cooling systems combined with renewable energy sources, storage (heat and electricity) and building or district integrated solutions in combination with smart grid technologies. Interoperable systems which integrate all different energy fluxes like electric energy sources and sinks, heat sources and sinks (including storage) and innovative control systems are required. The costs for different energy sources will vary depending on supply and demand. Smart solutions will offer best prices for investors and end-users. Construction processes are now part of the critical path to reach the final energy performance: any defect can lead to disorders and even pathologies which hamper the durability of the building performance. Several complementary routes can be envisaged, with the envelope and the technical equipment at the heart of the integration process: •
Prefabrication of standard units which facilitate field integration.
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•
New field integration process with more detailed internal performance control following elementary construction steps. New sensors can help check intermediate performance steps before commissioning (ex: blower-door test in combination with thermal imaging for air tightness) which, in turn, require collective work in the field.
•
Continuous improvement processes become part of a quality process which increases energy and comfort performances for new and refurbished buildings. RFID technology will improve productivity at the building site as well as the training of workers e.g. on the impacts of a wrong installation on the buildings’ performance.
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Starting at the design phase new standardized BIM exchange formats allow a continuous information flow towards a computer aided construction process.
Performance monitoring (both at commissioning and during the building life) is mandatory: it enables smart grid integration, allows users to oversee and control their own consumption and allows detecting inappropriate operating conditions. Moreover, conditional maintenance approaches can bring added value in guaranteed performance contracts. New IT solutions and embedded sensors will come from other fields of use (transportation for instance) as pervasive technologies that will be user centric. Performance management allows merging the best available technologies and processes to optimize both costs and performances of new or refurbished buildings. The ability to interact with smart grids will be mandatory. This implies not only connection capacities for energy supply including smart storage functionality, but also adaptable solutions for the buildings or districts themselves. The prediction of peak loads (e.g. by weather forecast) or support for low prices to load batteries for e-mobility will be implemented. Any changes of the boundary conditions in terms of changing energy production, energy demands, load cases, etc. will be handled. New learning control systems or control systems based on human behaviour may be introduced. Mitigation strategies for climate change can be part of this strategy. All these technologies are based on ICT. End of life: building demolition is an environmental issue which will grow under the pressure of deeper refurbishment. It can be addressed, both at design (reusable components) and demolition levels (reusable materials). The building industry is already involved in significant waste recovery (with a focus on concrete, metal and plastics). Innovation is expected in view of contributing both to the lowering of embedded CO2 and resource efficiency. Some of the ICT have an even broader context for future new or refurbished buildings and districts: •
Sensor networks are key components not only as standalone devices, but also embedded in smart Energy Consuming and Producing Products [EupP] The vision of these devices includes growing embedded intelligence, for instance product and repair information.
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•
User awareness, occupancy modelling and decision support now become more complex in a scenario with variable prices for energy and changing supply and demand. Highly integrated solutions are planned at the design phase and influence even the buildings’ end of life.
•
True interoperability will reduce redundant information and information affected with errors. Beginning at the design phase all components of the value chain can be enhanced by secure and long-term working data models and interfaces.
•
New data support systems provide reporting, data aggregation and statistical elaboration guidance and facilities (see www.concerto.eu). Regulation and standardisation e.g. for EPDs (Environmental Product Declarations) can benefit from it.
5. Conclusion This new Research and Innovation Roadmap gives dedicated R&D trajectories for each element of the value chain of the building sector: progressive market availability of technologies and processes will come from large scale demonstrations. They will show irrefutably that the best technical and cost performances can be reached on time for the market demand, thanks to integration processes taking care of the global optimization at building or even district level, and data sharing to help minimizing the interface risks inherent to any such complex system optimization process.
References PPP EeB (2010). "Energy-Efficient Buildings PPP. Multi-annual roadmap and longer term strategy". Prepared by the Ad-hoc Industrial Advisory Group. EUR 24263. E2BA (2011). "EeB PPP Project Review. FP7-funded projects under the first call". Prepared by E2BA (available online at www.e2b-ei.eu). E2BA (2012). "EeB PPP Project Review. FP7-funded projects under the 2010 and 2011 calls". Prepared by E2BA (available online at www.e2b-ei.eu). E2BA (2012). "Energy-efficient Buildings PPP beyond 2013. Research and Innovation Roadmap. Draft for open consultation". Prepared by the Ad-hoc Industrial Advisory Group (available online at www.e2b-ei.eu). EU Energy Roadmap 2050. COM(2011) 885/2. Buildings Performance Institute Europe - BPIE (2011). “Europe’s buildings under the microscope”. ISBN: 9789491143014.
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Feasible Energy Saving Potentials in Renovations for Residential and Service Building Stock Jaakko Vihola1, Juhani Heljo2, Antti Kurvinen3 The aim of the study behind this paper was to define feasible energy saving potentials of renovations in the 2010 Finnish residential and service building stock by 2050. This paper includes descriptions of the Finnish building stock and bottom-up calculation model called EKOREM, which was used to calculate different energy saving scenarios. Three different research methods that were used to determine the volume of potential renovations in the Finnish building stock are also described. Furthermore various reasons behind decisions to omit optional energy saving measures are discussed. Finnish building stock consumes almost 40% of the total energy use in Finland. Thus it should be one of the main focus areas when trying to achieve energy efficiency goals set by the European Union. The study showed that the feasible energy saving potential in renovations for the residential and service building stock in Finland is quite low compared to the rest of Europe. Feasible annual savings in heating energy from renovations varies from 0.2-0.7%. That means that cumulative savings in 2050 would be between 8-28 %. In theory, it is possible to save more energy than is considered feasible. Calculations were completed where the whole building stock was set to correspond to the 2010 Building Regulations of Finland. That resulted to about 40% of savings in the 2010 building stock by 2050. Low feasible saving potential is mainly due the fact that it usually pays to implement structural energy-saving measures only when the targeted elements are in a need of repair because of their physical condition. Attempts to achieve greater energy savings than can be reached with measures connected to scheduled renovations may multiply costs. Thus, the savings in energy costs will not necessarily cover the investments needed. In Finland, about 70% of the residential buildings are owner occupied. Owners cannot be forced to implement any energy saving measures that they don’t see reasonable or cannot afford. This comes to play especially in areas facing an uncertain future, and therefore financial possibilities to carry out expensive renovations are low. These are only few of the various reasons why energy-based renovations cannot be speeded up very much. Keywords: Energy consumption, Energy saving, Renovations, Residential and service buildings, Building stock 1
Researcher, M.Sc.; Department of Civil Engineering; Tampere University of Technology;
Korkeakoulunkatu 5 P.O.Box 600 FI-33101 Tampere Finland;
[email protected] 2
Researcher, M.Sc.; Department of Civil Engineering; Tampere University of Technology;
Korkeakoulunkatu 5 P.O.Box 600 FI-33101 Tampere Finland;
[email protected] 3
Researcher, M.Sc.; Department of Civil Engineering; Tampere University of Technology;
Korkeakoulunkatu 5 P.O.Box 600 FI-33101 Tampere Finland;
[email protected]
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1. Introduction At the end of 2006, the European Union pledged to cut its annual consumption of primary energy and greenhouse gas emissions by 20% compared to 1990 levels by 2020. Finland, as a part of the European Union, is required to fulfill these energy saving requirements as well. Building stock is a major contributor to energy consumption in Finland. In the year 2007 end usage of the energy in Finland was 307 TWh. Building stock’s share from this was 38% (Vehviläinen et al. 2010, p.13). Because of the high share, building stock should be one of the main areas of focus when considering how required energy savings and greenhouse gas reductions could be reached. This study focuses on feasible energy saving potentials of renovations in the 2010 Finnish residential and service building stock by 2050. In this case, feasible energy saving potential means savings achieved by energy saving measures which are carried out within scheduled renovations and are considered technically approved and economic. Plenty of earlier research has focused on the economics of energy efficiency investments. It seems that even at the present level of energy prices and without implementation of large scale policy instruments, many of energy saving measures are profitable to carry out (Amstalden et al. 2006). Profitability of different measures can increase even more if different kinds of cobenefits are considered in addition to energy-related benefits (Jakob 2004). Co-benefits include, for instance, improved indoor air quality and protection against external noise. The energy saving potential calculations were made using EKOREM-calculation model (Heljo 2005). Four different scenarios were studied and the results show that feasible energy saving potential in renovations is smaller than expected and might cause some serious challenges when considering the goals set by the European Union. In the UK, similar results have been achieved regarding of CO2 emission reductions (Johnston et al. 2004). Because of complex nature of the building stock and its energy consumption, this study focuses only on energy saving measures that consider buildings’ envelope, ventilation system and hot water usage. Electricity consumption is only observed as a part of ventilation renovations. Heating system changes, new production saving potentials and energy consumption affected by user behavior are excluded from this study. Globally thinking results might vary greatly depending on which country is studied. Savings potential in energy consumption and greenhouse gas emissions are highly dependent on characteristics of the studied building stock and climate conditions. For example, distribution of building types and age as well as heating/cooling systems used are all factors when trying to estimate feasible saving potentials. In Finland, where the climate is cold, most of the energy saving in old buildings is achieved by increasing isolation layers of building envelope within scheduled renovations or by less expensive HVAC adjustment measures. In hot climate conditions, completely different problem field must be considered. There main focus should be directed to how to minimize cooling demand of buildings. This study has been made using Finnish climate data and building stock information, and thus the results are not to be generalized globally without further examination.
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Finland is situated in northern hemisphere between the latitudes 60° and 70°. The average temperature in Helsinki (capital of Finland) on the southern coast of Finland is approximately 6°C. Difference in climate conditions between seasons is remarkable changing from hot summers to cold snowy winters. The Finnish residential and service building stock is one of the youngest in Europe. Almost 70% of the stock has been built between 1970-2010 (Figure 1). 72% of the stock consists of residential buildings where single family houses form the largest group (40% of the stock). The age distribution of the building stock is the reason why big part of the building stock is in a need of renovation.
Figure 1. The Finnish residential and service building stock in the year 2010. Data is categorized into five different groups which represent different building types. Inside each of these five groups data is further divided to show when buildings have been constructed. (Statistics Finland) Heating system distribution, especially in single family houses, is highly diversified. Most of the heating energy demand in single family houses is met either by wood/pellet, oil or electricity. Because of the new building regulations in the new production, focus will move strongly towards ground source heat pumps and other systems that utilize renewable energy resources. Rest of the residential and service building stock is almost exclusively connected to district heating except in the rural areas where service is not available. In 2010 the Finnish residential and service building stock was using energy about 91 TWh. Residential buildings’ share of this was approximately 64% and the rest 36% was consumed in different kind of service buildings. In residential buildings, most of the total energy consumption goes to heating of spaces and hot water. In service buildings, proportion of electricity consumption is noticeably higher because of the lightning requirements and demand of effective cooling caused by large amount of electric devices and people using the spaces.
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The objective of this paper is to give a scientific estimation of feasible energy saving potentials in the Finnish residential and service building stock. Whenever saving potentials are referred to, for example by the politicians or the press, usually the magnitudes are way off. Statements are often based on sophisticated guesses rather than data produced by scientific methods. That is because of challenging nature of the building stock as a research object and the lack of statistical data considering renovations in the building stock.
2. Research Methods Analysis of energy saving potentials was made by using bottom-up calculation model called EKOREM developed in Tampere University of Technology (Heljo et al. 2005). EKOREM is a building stock calculation model which can be used to determine energy consumption and greenhouse gas emission of the building stock in different cross-section years. Calculation method of the model is based on the part D5 (2007) of the National Building Code of Finland called “Calculation of Power and Energy Needs for heating of Buildings” (Finnish Ministry of Environment 2007). In the model, building stock is divided in building type categories similar to used by Statistics Finland so that official statistical data can be easily used in calculations. Inside each building type buildings are further divided to age groups so that different groups can be given different kind of describing technical base values (for example U-values of different structural elements), which represent the methods of construction in each era as an average. The main purpose of the EKOREM-model has been to create data for the EU-reporting needs to show how development of the National Building Code of Finland has reduced building stock’s energy consumption and greenhouse gas emissions. Besides this, many regional studies have also been made.
2.1
Studied Energy Saving Measures
In this study, the following energy saving measures were included: adding insulation to external walls, adding insulation to roofs, improving energy effectiveness of windows, improving air tightness of building envelope, improving/adding heat recovery unit to ventilation systems and installing flow meters to decrease consumption of hot water. When trying to estimate energy saving potential in renovations of the building stock, studies must be based on an assumption that different building elements are only renovated when they are in need of a repair because of their physical state. Carrying out renovations, considering only energy saving aspect and without real technical or physical needs will lead to significant additional costs (Heljo & Vihola 2012). In figure 2 is simplified linear presentation which shows how energy saving measure’s share of total costs increases if trying to implement it before there is a need of renovation because of the physical state of the structure. From the economic point of view, energy renovations are most profitable when carried out within scheduled renovations.
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Figure 2. Simplified presentation of how additional cost of energy saving measure grows when trying to implement a measure earlier than is required from the technical and physical point of view. (Heljo & Vihola 2012)
2.2
Volume of Renovations
To know the volume of different kind of completed renovations is essential for estimating building stock’s energy saving potentials. Within this study, three different estimations were created about the volume of renovation projects in the complete national building stock. First estimate is based on the very comprehensive research made by Technical Research Centre of Finland (Vainio et al. 2002). This research claims that approximately 2% of the studied building elements are renovated yearly (Figure 3). When comparing the results of this study to data of today, it shows that the volume of renovations has stayed almost the same.
Figure 3. Annual energy refurbishments in the Finnish building stock in the year 2000. On average about 2% of measures are carried out annually. Windows are being improved more often than that. (Vainio et al. 2002)
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Other way of predicting the volume of refurbishment projects was to estimate life cycles of different building components and then to link these estimations with the building stock data. For example, window areas for different building types and different age groups can be found from the EKOREM-calculation model. Window area of apartment buildings by the year of construction can be found from figure 4.
Figure 4. Window area in apartment buildings by the year of construction in the Finnish building stock as presented in EKOREM calculation model. (Heljo & Vihola 2012) Different renovation profiles of structural elements were created for this study. In figure 5 is presented an estimation in which age windows are usually renovated.
Figure 5. Histogram representing the age distribution when windows are usually renovated in apartment buildings. (Heljo & Vihola 2012) When combining these two sets of data, one can make a theoretical distribution of window renovations as shown in figure 6. Some of the windows go through two rounds of renovations before the year 2050. In Finnish climate conditions this basically means that in a first round really old double-glazed windows (U-value=2,7 W/K,m2) are changed to triple-
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glazed windows (U-value = 1,4-1,8 W/K,m2) and in the second round of renovations these are replaced by four-glazed windows (U-value = 0,85 W/K,m2).
Figure 6. Theoretical distribution of window renovations in the Finnish building stock based on combining the data presented in figures 4 and 5. This can be used as an estimate to calculate feasible energy saving potentials. (Heljo & Vihola 2012) This type of an examination is only possible in the case of windows and external walls. That is because adding insulation to roofs is not in all cases tied to scheduled renovations. Same goes for ventilation renovations. Third source of information was so called “Expert Day” which was held during the project. Participants were from different organizations from the fields of construction research, consulting and planning. As a result following table (Table 1) was created of different energy saving measures. Table 1. Volume of different energy saving measures in different building types in the Finnish residential and service building stock that are done already or will not be done by 2050 according to “Expert Day”. Experts' estimations of implementation of energy saving measures 20102050
Window Exchange
External walls' supplementary insulation
Roof's supplementary insulation
Improving air tightness of building envelope
Adding heat recovery unit to ventilation system
Installing flow meters to reduce hot water consumption
Done
Will not be done
Done
Will not be done
Done
Will not be done
Done
Will not be done
Done
Will not be done
Done
Single family houses
15 %
20 %
15 %
40 %
20 %
15 %
5%
70 %
30 %
10 %
100 %
Row houses
15 %
10 %
15 %
40 %
5%
20 %
5%
70 %
Apartment buildings
15 %
15 %
8%
40 %
3%
75 %
5%
80 %
5%
80% / 20%
10 %
Commercial and office buildings
15 %
15 %
10 %
50 %
0%
75 %
5%
80 %
50 %
5%
100 %
Public service buildings
15 %
15 %
10 %
50 %
0%
75 %
5%
80 %
50 %
5%
100 %
Will not be done
5%
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Table represents the perception of the experts considering different energy saving measures, and in which scale they might be implemented to the building stock in the future. Feasible energy saving potential is reduced by the fact that some percentage of the measures has already been done and some percentage will never be done because of various reasons. Potential volume of different measures by 2050 can be easily calculated by reducing from 100% the amount of measures already done and the amount of measures that will not be done. There is a significant amount of uncertainty relating to ventilation renovations. Expert opinions considering on how many of heat recovery unit installations will not be done by 2050 vary from 20 to 80%. Pessimistic opinion of 80% is based on the assumption that technical solutions of ventilation renovations will not be developed profitable and easy enough to put into practice. Calculations of feasible energy saving potentials have been made by using more optimistic view of 20%.
2.3
Reasons for Omitting Energy Saving Measures
One of the main topics during the Expert Day was figuring out reasons holding back implementation of energy saving measures. Plenty of different factors were found and those can be categorized to five groups. First group includes problems regarding properties of buildings. Building can be too young or in good condition so renovations are unnecessary. In some cases, building might be close to end of its life cycle so there is no reason to renovate. There are plenty of buildings which are considered as architectural monuments and because of that they are protected from any renovations that might change the appearance of the building. There are also buildings that are planned for only temporary use. (Heljo & Vihola 2012) In second group there are buildings that are situated in areas where economic outlook is bad. Situation there is that even the most profitable energy saving measures are not implemented because funding is not available. Usually when an energy-saving measure is implemented within scheduled renovation additional cost caused by the measure varies around 5-15%. (Heljo & Vihola 2012) In third group, there are problems regarding lack of know-how and sceptical attitudes towards energy saving measures. These kinds of problems are, for instance, ones regarding ownership of the buildings. 75 % of the Finnish residential building stock is owner occupied which means that there are lots of decision makers and they cannot be forced to implement energy saving measures which they do not see profitable. One of the major problems is lack of experiences considering energy renovations. This reflects straight to level of know-how in the field of construction. Used technologies might be strange and not understandable enough and at the same time there might be a feeling of uncertainty regarding physical functionality of the new structure. Old structural components are also often considered valuable. In most projects, there is not enough time or resources to go through positive effects of energy renovations. (Heljo & Vihola 2012)
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Fourth group includes technical and architectural difficulties. In some cases, energy saving measures are hard to carry out from the technical perspective. Especially in old buildings renovations linked up to building’s envelope are hard to implement while retaining architectural and physical properties of the building. (Heljo & Vihola 2012) Fifth and final group includes problems that are connected to profitability and the lack of resources. Usually there is lots of contradictory information available regarding of the profitability of energy saving measures. False information is usually caused by too shortsighted way of evaluating the effects of the energy saving measures. Every decision-making situation that is connected to large scale renovations should involve life cycle analysis of the building to make sure that the most profitable measures are implemented (Kurvinen et al. 2012).
2.4
Different Calculation Scenarios
When the volume of energy saving measures has been estimated, it is possible to use EKOREM-model to calculate energy saving potentials. For the study, four different calculation scenarios were created. These scenarios are: 1. Basic development where decrease in building units is included but different energy saving measures are not put into practice. Basic development must be known so that the saving potential of energy renovations can be calculated. 2. Theoretical saving potential which is calculated on an assumption that life cycle of the building elements determine the moment of different refurbishment measures. Limitations set by information from the Expert Day have been taken into account. 3. Calculation where the volume of refurbishments is based on realization of energy-saving measures in the past. Limitations set by information from the Expert Day have been taken into account. 4. Theoretical maximum saving potential where whole 2010 residential and service building stock has been refurbished to be equivalent to current Finnish National Building Code requirements for new production by 2050. Scenarios 2 and 3 describe situations that are considered feasible. However, they are challenging as well. In calculations an assumption has been made that whenever scheduled renovations are carried out profitable and technically valid energy saving measures are implemented. Yet it has been estimated that at the present time only half of the time that actually realizes. Scenarios 1 and 2 are made for the comparisons. Basic development without energy saving measures is presented so that feasible savings achieved by energy saving measures could be calculated. Theoretical maximum is possible to reach in single projects where conditions are right, but several factors mentioned before prevent renovations of such a large scale in building stock level.
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3. Results and Discussion The results of the different calculation scenarios have been presented in the figure 7. In the year 2010 the Finnish residential and service building stock is using energy 91 TWh/year. Because of decrease in building stock units, this value is reduced to 56 TWh/year by 2050. However, this reduction in the energy consumption cannot be counted as savings because disposed buildings will be replaced by new production at the same sites or somewhere else. It has been estimated that nearly 30% increase in the residential and service buildings stock is needed by 2050 to cover space requirements set by growth of population and increased demand of services (Vehviläinen et al. 2010, p. 44).
Figure 7. The results of the different calculation scenarios. Scenarios considered feasible are number 2 and 3. Reduction of energy consumption caused by decrease in the 2010 building stock is also represented in the figure. The calculations show that feasible energy saving potential in renovations is somewhere between 9-11 TWh by 2050. This is approximately 20% from the basic development level (56 TWh) where energy saving measures were not implemented. Annual saving potential is approximately 0,5% per year. If the whole 2010 residential and service building stock were renovated to correspond the requirements for new production presented in the national building code of Finland, then by 2050 its energy consumption would be 36 TWh. Klobut and Tuominen (2010) estimated energy savings potential of nine European Union countries’ residential building stock (Finland included). They claimed that on average in these countries 10% energy savings could be reached by 2020 and 20% by 2030.
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In table 2, savings from different energy saving measures have been presented separately. Most savings can be achieved through improving heat recovery of the ventilation. However, the problem is that the prediction of ventilation renovation volume includes most uncertainty. The rise in the use of electricity can be explained with the fact that usually when building’s quality standard is improved it also means implementing new technical systems and adjustments of old ones, which increase the electricity consumption in the building. In this study, only electricity consumption related to ventilation renovations is considered. Electricity consumption rises because old natural ventilation systems are replaced with mechanical systems equipped with heat recovery unit. Regarding of measures related to building envelope, it seems that improving energy effectiveness of windows and external walls will have the biggest effect on building stock level. Table 2. Feasible energy saving potentials of different energy saving measures in the 2010 Finnish residential and service building stock by 2050 Measure
Savings
Roof
2,0 %
External Walls
4,3 %
Windows
5,1 %
Doors
0,2 %
Ventilation
9,3 %
Hot Water
0,7 %
Real Estate Electricity
-1,6 %
Total
20,1 %
4. Conclusion The calculation results indicate that it is more difficult to save energy in the Finnish building stock than in Europe on average. By 2050 the feasible energy saving potential of the 2010 Finnish residential and service building stock is approximately 20%. This estimation is based on the current volume of renovation projects in the Finnish building stock. For various economic and technical reasons, it seems highly unlikely that energy-based renovations could be speeded up much. However, it should be noted that primary energy saving potential is much bigger than 20%. On July 2012 Finland adopted new energy effectiveness regulations for new production. These regulations present new challenges for new production by the form of requirement called E-value. E-value requirement varies depending on a building type and in single family houses depending on building’s size. Basically what regulations did was to set E-value limits (kWh/sqm/year) that building must fulfill. The most significant change related to calculation of the E-value are primary energy factors. These factors are used to multiply energy bought in the building with a specific factor depending on how energy is produced. These primary energy factors are strongly favoring the use of renewable energy resources. At the same time they will steer towards low-energy buildings if electricity is used as a primary source of heating energy. In the future this will surely change heating system distribution in the Finnish building stock in a way that primary energy savings will be larger than 20%.
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References Amstalden, R., Kost, M., Nathani, C., Imboden, D. 2006. “Economic potential of energyefficient retrofitting in the Swiss residential building sector: The effects of policy instruments and energy price expectations”. Energy Policy 35 (2007). p. 1819-1829 Finnish Ministry of Environment. 2007. National Building Code of Finland, part D5: “Calculation of power and energy needs for heating of buildings” (in Finnish). Helsinki. 72 p. Heljo, J., Nippala, E., Nuuttila., H. 2005. “Energy Consumption and Carbon Dioxide Emissions in Finnish Buildings” (in Finnish). Tampere, Tampere University of Technology. Department of Construction Management and Economics. Research report. 112 p. Heljo J, Vihola J. 2012. “Feasible energy saving potentials in renovations of building stock” (in Finnish). Tampere, Tampere University of Technology. Department of Construction Management and Economics. Research report. 84 p. Jakob, M. 2004. Marginal costs and co-benefits of energy efficiency investments, The case of the Swiss residential sector. Energy Policy 34 (2006). p. 172-187 Johnston, D., Lowe, R., Bell, M. 2004. “An exploration of the technical feasibility of achieving CO2 emission reductions in excess of 60% within the UK housing stock by the year 2050”. Energy Policy 33 (2005). p. 1643-1659. Kurvinen A., Heljo J., Aaltonen A. 2012. ”Economic decision-making in suburban development projects” (in Finnish). Tampere, Tampere University of Technology. Department of Construction Management and Economics. Research report. 147 p. Tuominen P., Klobut K., Tolman A. 2010. ”Energy Savings Potentials in the Building Stock of nine Member States of European Union”. Proceedings CLIMA 2010 Congress CD. CLIMA 2010. 10th REHVA World Congress “Sustainable Energy Use in Buildings” 9-12 May 2010. Antalya, Turkey. ISBN: 978-975-6907-14-6 Vainio, T., Jaakkonen, L., Nippala, E., Lehtinen E., Isaksson, K. 2002. ”Renovations in Finland 2000-2010” (in Finnish). Espoo, Technical Research Centre of Finland. 60 p. Vehviläinen, I., Pesola, A., Heljo, J., Vihola, J., Jääskeläinen, S., Kalenoja, H., Lahti, P., Mäkelä, K., Ristimäki, M. 2010. ”Energy Usage and Greenhouse Gas Emissions of Built Environment” (in Finnish). Sitra’s Studies 39. 125 p.
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Daylighting Design and Simulation: Ease of use analysis of digital tools for architects Konrad Panitz1, Veronica Garcia-Hansen2 ABSTRACT Good daylighting design in buildings not only provides a comfortable luminous environment, but also delivers energy savings and comfortable and healthy environments for building occupants. Yet, there is still no consensus on how to assess what constitutes good daylighting design. Currently amongst building performance guidelines, Daylighting factors (DF) or minimum illuminance values are the standard; however, previous research has shown the shortcomings of these metrics. New computer software for daylighting analysis contains new more advanced metrics for daylighting (Climate Base Daylight Metrics-CBDM). Yet, these tools (new metrics or simulation tools) are not currently understood by architects and are not used within architectural firms in Australia. A survey of architectural firms in Brisbane showed the most relevant tools used by industry. The purpose of this paper is to assess and compare these computer simulation tools and new tools available architects and designers for daylighting. The tools are assessed in terms of their ease of use (e.g. previous knowledge required, complexity of geometry input, etc.), efficiency (e.g. speed, render capabilities, etc.) and outcomes (e.g. presentation of results, etc.). The study shows tools that are most accessible for architects, are those that import a wide variety of files, or can be integrated into the current 3d modelling software or package. These software’s need to be able to calculate for point in times simulations, and annual analysis. There is a current need in these software solutions for an open source program able to read raw data (in the form of spreadsheets) and show that graphically within a 3D medium. Currently, development into plug-in based software’s are trying to solve this need through third party analysis, however some of these packages are heavily reliant and their host program. These programs however which allow dynamic daylighting simulation, which will make it easier to calculate accurate daylighting no matter which modelling platform the designer uses, while producing more tangible analysis today, without the need to process raw data.
1
Research Student; Lighting and Colour Lab, School of Design; QUT; 29 Glenwood Drive, Morayfield, 4506;
[email protected]. 2 Lecturer in Architecture; Lighting and Colour Lab, School of Design; QUT; GPObox2434, Brisbane, 4001, QLD, Australia;
[email protected]
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Keywords: Daylighting, Daylight simulation, Climatic base daylight metrics, Radiance, Daysim, Diva
Introduction: Within the built environment, evidence-based design should be pursued either by looking at precedence works or the analysis of projects either physically (through observation and rules of thumb) or digitally (computer simulation) as they provide tangible information in terms of indoor environmental quality (IEQ) of the project. Research into the tools commonly used by architects has revealed that in terms of analysis, either digitally or physically, outputs, useability, efficiency and accuracy can be somewhat varied (Attia et al., 2009, Mardaljevic, 2001). The two main issues, as highlighted by Attia et al. (2009), are firstly the usability and information management of interface, and secondly the integration of intelligent design knowledge-base (Attia et al., 2009). According to a survey by Attia et al. (2009) the main software’s used for building performance analysis are Ecotect, eQUEST, Energy Plus and Energy Plus for SketchUp (plug-in), and IES VE (Revit plug-in), etc. Evidence based design is particularly important for daylighting design in buildings, especially in climates such as those present in Australia (tropical and subtropical). Main issues with building in these climates are overheating and glare, resulting in buildings with tinted glassed and/or overshaded openings which reduce daylight levels availability. Main decisions that affect dayligthing (availability, orientation, building context, shading, location and shape of windows, etc) are decisions made by architects, and therefore visualization and understanding of how these design decisions could affect daylighting performance is paramount. Thus the need for easy to use daylight simulation tools for architects. Galasiu and Reinhart (2008) survey of current daylight design practices of design teams (in the USA, and Canada), found that during the early design stage practitioners tend to rely on experience from previous work and rules of thumb and that computer simulations are increasingly being used during the design development stage. Participants reported the use of up to 39 different softwares for daylight analysis, although 62% were based on radiance. With industry focus on Build Information Technology (BIM) design decisions can be changed quickly, effectively and verified within the digital model for costs, time and effectiveness. Any advancement in daylighting analysis needs to be integrated into BIM technologies so that architects and other professionals can easily integrate their models into the analysis software. Current analysis software for BIM has been designed as an add-on premise where a third party program or plug-in that supports a variety of file types performs the analysis of the building. Due to the many different file types within industry a universal file type such as an IFC (Industry Foundation Classes) has been developed. Conversion to IFC needs to contain the base information of the model such as, location, orientation and materials. Currently most IFC’s do not contain this information (Lee et al., 2003). This leads to architects only using analysis software that’s compatible with their proprietary modelling solutions or rely purely on rules of thumb for daylighting. The purpose of this paper is to evaluate the usability of daylighting simulation software from the architect or designer’s point of view in the particular context of Brisbane, Australia. This
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paper will explore daylighting metrics, sky components, building rating/certification guidelines, built information modelling and IFC’s while exploring the capabilities of digital analysis software. The development and understanding of all these components play a vital role in the future of daylight analysis in architecture. This paper highlights the need for evaluation of metrics using today’s analysis software on a project, the capabilities and benefits of such analysis, as well as an exploration on the processes and issues that arise when architects use unfamiliar complex daylighting software. The present state of daylighting and industry The integration of light into a building is a fundamental part of creating space. Daylighting has numerous psychological and physiological effects on buildings’ occupants; still, it can have an adverse effect (i.e. glare, overheating) on the indoor environmental quality of that space if special care is not taken into the daylighting design. Galasiu and Reinhart's survey on daylighting design practice among design teams with interest in sustainable design found out that rules of thumb and daylighting factor (DF) are the main prediction methods for daylight (Galasiu and Reinhart, 2008). However, DF has it short comings as proved by studies on post occupancy evaluations (Thompson, 2011, Mardaljevic, 2011, Lee and Guerin, 2010). These studies show a general disparity between what is considered acceptable between performance guidelines on daylighting and acceptable indoor illuminance by occupants. Within the context of Brisbane there are currently 2 main documents that architects use that qualify daylighting design, National Construction Code (NCC): Building Code of Australia (BCA), and Green Star (GS) rating system (Australian Building Codes Board, 2011, Green Building Council of Australia, 2008, Standards Australia, 2006). These documents outline a set of performance standards and metrics which architects and professionals within industry should achieve usually based on DF. DF is defined as “the ratio of internal illuminance to the external illuminance under a CIE overcast sky.” (MOON, 1942) It is a static metric measured on one day of the year as representation of the worst-case scenario. Nevertheless, there are new dynamic metrics (Climate based daylight modelling- CBDM) that predict luminous quantities using realistic sun and sky conditions derived from standardized meteorological data These metrics are Daylight Autonomy (DA), Useful Daylight Illuminance (UDI) and Daylight Availability (Dav) (Mardaljevic, 2001, Reinhart et al., 2006, Nabil and Mardaljevic, 2006) (Metrics are described under the assessment of daylighting simulation section). New metrics for daylighting design could change the way in which architects and other professionals run analysis providing accurate legible data that could easily be applied to the design process by allowing more exploration and thus better designs. These new climate based daylight metrics (CBDM), are much more informative to professionals and disarmingly simple. Though, currently there is no consensus on targets let alone which metric should be used in standards (Nabil and Mardaljevic, 2006).
Methodology
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This paper evaluates the usability of daylighting simulation software’s from the designer’s point of view. To this end, firstly, it identifies the simulation tools and methods most currently used by architects in Brisbane, to be selected for this study. Secondly, tests and compares their performance against real measurements from a real space (point in time simulations). And finally, qualitatively assess the “friendliness” of application of simulation software into the workflow of architects.
Selection of tools A simple survey of architectural firms -within the greater Brisbane area- was performed to collect data on current technologies, services and methods used in design analysis. The firms were invited to contribute information on: 1- what methods they used to make models for design analysis, 2- if was daylighting considered in their analysis, 3- what programs methods or services were used to generate data on daylighting. MODELLING SOFTWARE
ANALYSIS SOFTWARE
Figure 1. Greater Brisbane Architectural Firms Process and Method for design and analysis for daylighting As seen in Figure 1, a significant portion of the firms surveyed use Revit and SketchUp for their 3D model making process, whilst the only industry recognized method for daylighting analysis used was 3ds Max. Due to the lack of recognised industry tools used within Brisbane firms, well known software’s for daylight analysis such as Ecotect and Diva are added to the list of software’s to be assessed. Ecotect is widely accepted as a method for analysis and Rhino/w Diva plug-in is currently leading the way for development of daylighting software overseas. In addition to Ecotect and Diva, a study by Reinhart and Breton (2009), compared two popular daylighting software packages, Daysim and Radiance alongside 3ds Max. The study found that Daysim and 3ds max were capable at achieving comparable results to radiance and therefore could be used for daylighting analysis (2009). In summary, when considering the results of the survey and prior research, the software’s used for digital model making for this research are SketchUp and Revit. The 3D models are then analysed using 3DS Max (Design Version), Ecotect (w/ Daysim and Radiance), SketchUp w/ Experimental Daysim Plug-in Su2ds and finally Diva through the use of Rhino (modelling making software).
Assessment of daylighting simulation tools
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The assessment of the selected simulation tools has the following steps: 1- a real building is selected for analysis and 3d models of the building are constructed, 2- 3D models are imported to the different simulation tools for analysis. 3- DF, CBDM and point in time simulations are performed and 4- the results of point in time simulations are then compare to measured horizontal Illuminances taken of the real space for calibration. 1- A studio space on a university campus in Brisbane was recreated within both SketchUp and Revit for analysis and modelling. The room was selected based on the most equatorial facing room within the building with good daylighting. Dimensions were kept as identical as possible such as wall thickness, window heights and sizes, etc. to retain accuracy. The model was oriented from true north by +35 degrees to comply with aerial photos of the site. Neighbouring buildings were also added in the model. Reflectances for the building materials are 60% for ceiling and floors, 40% for walls, and 80% transmittance for windows. The geo-location, climatic data was gathered and imported into both Revit and SketchUp. The climatic data was IWEC (International Weather for Energy Calculation) weather data for Brisbane. 2- The model was altered and redrawn were necessary within software packages to correct for errors in the export/import process but also to effectively document to process of “build-ability”. These programs are also run to produce annual data such as DA, continuous DA, UDI and DAv, as well as Point in Time illuminance measurements at 9am, 12pm, 3pm and 5pm (September 28th) as well as a DF for that day. These Metrics are as defined as follows. 1. DF: ratio of internal illuminance to the external illuminance under CIE overcast sky 2. DA: percentage of the year when an interior illuminance threshold is achieve by daylight alone 3. UDI: percentage of the year when a target range of illuminances (e.g. 100 to 2000lux), no too low (for visual task performance) and not high causing issues with glare or heat gain., is achieved. 4. DAv: is a variation of UDI accounts for partial daylight within its calculation and highlights areas within the room with thermal/visual discomfort (10 times the target illuminance). 3- Illuminance measurements of the studio space: A Minolta T10 illuminance meter with 9 sensors was set up in the studio to measure the internal horizontal illuminance (28th of September) at 1 minute intervals and diffuse and direct external illuminance at 1hr intervals. The placement of sensor in the space can be seen below in Figure 2. 01
OUTSIDE
ILLUMINANCE
METER
2
3
4
7
6
5
8
9
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Figure 2. Sensor Grid, Light Meter Locations 4- Ease of use analysis of the different software was done via observations on legibility/output, speed, ease of use, and importing/exporting data capability with the aim to assess differences in workflow between programs.
Results Measured horizontal illuminances and Point in time modelled illuminance for the
studio space Figure 3 shows measured average horizontal illuminance values for 9am, 12pm, 3pm and 5pm. These results are compared with simulations performed for the same day and times for the following tools and sky types: a) 3ds max with haze driven sky, with Perez sky and with , Perez sky tuned to mirror the clear sky (measured) on that day via controlling direct illuminance as well as diffuse horizontal illuminance, b) Radiance with uniform sky, sunny sky and intermediate sky and finally diva with sunny sky and sunny sky with no sun. , e) radiance with sunny sky. The results show that radiance simulations (through ecotect) with sunny sky most closely represent the internal illuminance levels and daylight distributions throughout the day obtained with the light monitoring. The curves from 3ds max with Perez sky simulations closely follow the measured values for half of the day, while direct sunlight is not present in the room. Diva simulations with sunny day do not follow the distribution pattern during the day, specially underestimating performance early in the morning and late in the afternoon. Because of the daylighting issues presented in the studied space (incoming direct sunlight in the afternoon), all the other simulations that use sky types with no sun, did not follow the illuminance distribution throughout the day or achieve similar lighting levels specially in the afternoon. It is not the aim of this paper to calibrate different simulation tools with measurements of real spaces, but rather to try to show, from the perspective of an architect how a simple step as choosing the sky type can have great implications on the overall results in the simulation.
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Figure 3. Comparison between measured illuminance levels in the studio space and modelled illuminance levels by different simulation tools for 28th of September
Climate base metrics and Daylighting factor simulations Certain packages are able to perform more metric simulations than others, a list of which can be seen in Table 2 below. Rhino w/ Diva was the most comprehensive being able to generate data on, DF, DA, DAv and UDI. For the testing of DIVA the SketchUp model was used due to IFC issues when trying to import the Revit model into Rhino (host program for the DIVA plugin). Table 1. Time Period and Annual Data Abilities within Selected Software 3DS Max DF
**
DA DAv UDI DAcon*
* * *
Ecotect
Radiance
Daysim
Diva
Su2ds
***
*** *** *** ***
* Raw format requires processing through excel or other software. ** Prone to inaccuracy *** Not able to be tested due to incompatibility with current software
For 3DS Max climate-based simulations like DA, DAv, UDI and DAcon are convoluted, and requited a lot of manual inputs. For this reason it was not included in the ease of use comparison analysis. While radiance, which is a rendering program, in its base form can calculated data over a time period but cannot calculate dynamic data, therefore cannot calculate climate based. However its algorithms are implemented into other analysis software’s. Su2ds a direct plugin to Daysim for SketchUp required a complicated manual entering of analysis grid points via their x,y,z co-ordinates, making it easy for simple models, but impracticable for larger models so wasn’t tested. Table 2. DF and Climate-based simulation comparison within Selected Software 3d Model Revit
SketchUp
Simulation Tool Ecotect Daysim Ecotect Daysim Diva
DF 5% 4% 1%
DA 98% 71% 93% 62% 28%
UDI 69% 66% 60%
Dav 24%
The simulations from the different software’s show very different results. UDI 100-2000 shows some correlations between all the diva and Daysim plug in for Revit and Sketch up. While DA (with a target of 300lux) results do not compare closely between Daysim, Diva, and specially the results for Ecotect (Daysim plug in). The error in Ecotect could be related to the DA calculations being locality based the algorithm is only applicable at latitudes of 40-60 degrees +/-degrees from the equator. Brisbane is located at 25 degrees from the equator, so Ecotect cannot be used for DA calculations. Another issue is the skylights (present in the
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space and modelled in the 3D models) seemed to be more effective in the Revit model, resulting in higher results. The differences between Diva and Daysim on the other hand, could be explained through the method used for Daysim analysis, which involved exporting data from Ecotect. Ecotect was used as a medium to generate data for Daysim. And then, painstaking imputing a sensor grid data manually using scripting (steps that are somewhat outside the skill set required from architects). To obtain more comparable results between all the software’s, more testing, and further study of the models and simulations tools is necessary. However, for this research is a first step in analysis these tools, and from the architect/designer point of view (including skill sets).
Graphics Within these programs, the viewports can also be quite ridged, often appearing in either as a fixed 2D image of a 3D space, as seen in the Radiance Image in Figure 4. Or a plane which hovers at the workplane within a 3d model as seen in Figure 4. Programs such as Daysim produce data mostly through spreadsheets as raw data, and 3ds max and diva have this same function for more in-depth analysis outside the parameters of what each program’s view portal or false colour images can generate. Ecotect can input analysis data, however this data needs be in a .dat file type so Ecotect can interpret and create images, which was the case for Daysim/Diva, but not 3ds Max.
3ds Max
Ecotect
Radiance
DIVA
Figure 4. Examples of view portals from different softwares and different metrics/analysis
Analysis of ease of use This section describes the analysis and observations of the process involved in the running of analysis for both point in time illuminance simulations and climatic data simulations.
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Table 3. Modelling, Editing and Host Programs for Analysis: Observations Software
Export
Import
Analysis
Modelling
Required
Options
Options
Plug-Ins
Complexity
Familiarity
3ds Max
.FBX, .3DS, .DWG, .DGN, .DXF, .SKP, .XML
.FBX, .3DS, .DWG, .DGN, .DXF, .SKP, .XML
Yes
High
Frequent Use
Revit
.FBX, .3DS, .DWG, .DWF, .DGN, .DXF, .XML, .IFC .3DM, .DXF, .DWG, .DGN, .SLDPRT, .FBX, .3DS, .RAW, .X, .SKP .FBX, .3DS, .DWG, .DXF
.DWG, .DGN, .DXF, .SKP,
Yes
High
Frequent Use
.3DM.DXF .DWG.3DS .RAW.X .WMF.TXT .FBX.PLY
Yes
High
Infrequent Use
.3DS, .DWG, .DXF,.SKP
Yes
Low
Infrequent Use
Rhino
SketchUp
Notes:
Complex program interface with multiple parameters to alter models requires prior experience Works well exporting to 3ds Max, complex program requires prior experience Not a common tool for modelling within Australia, simple program in terms of interface and usability
Easy to use and install plug-ins. Exporting Directly into Radiance and Daysim requires experience with coding language and techniques.
Table 4. Analysis Software Observations Part 1 of 2 Software 3ds Max
Sky CIE Perez Haze
Renderer Metal Ray
Raytracing Forward and Backward
Ecotect
CIE Perez CIE Perez
none
Split Flux Method Backward
Daysim
Perez
none
Diva
CIE Perez
none
Radiance
Radiance
Backward with Daylight Coefficient Backward with Daylight Coefficient
Metrics DF, DA, DAv, UDI. DF, DA. DF.
Speed FAST SLOW SLOW SLOW FAST FAST FAST
DF, DA, UDI.
FAST SLOW SLOW
DF, DA, DAv, UDI
FAST FAST FAST FAST
Sky Models Overcast Clear Perez
Importability Triangulation, great at retaining surface integrity.
Uniform Overcast Sunny w/ Sun Sunny w/o Sun Intermediate w/ Sun Intermediate w/o Sun Overcast Sky Uniform Sky Perez
Triangulation, loses surface integrity. Ecotect exports a dedicated radiance file for analysis. All model errors contained within modelling software.
Clear Sky w/ Sun Clear Sky w/o Sun Cloudy Sky w/ Sun Cloudy Sky w/o Sun Uniform Custom (Perez) Perez
As above due to Daysim being built upon radiance. Some minor triangulation, North point data was lost on import. Most comprehensive Import options with fewest issues.
Table 4. Analysis Software Observations Part 2 of 2 Software
3ds Max
Editing Imported Geometry Easy, Fast
Model Editing Interface Powerful, efficient, but complex
Analysis Interface
Analysis Viewports
Outcomes
Notes
Complex
Full 3D & 2d Viewports & 3D
DF on Workplanes, Illuminance on Workplanes
Raw data needs to be calculated though excel spreadsheets. Unique communication
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images
and surfaces. Raw data False Colour images Metrics and illuminance calculated on Workplanes
Ecotect
Difficult, Slow
Difficult, unlike modelling software
Simple
Full 3d & some 2d Views & 3D images
Radiance
n/a
n/a
Simple within Ecotect, Complex Standalone
3D images
Illuminance on surfaces. (3D Image) False Colour images
Daysim
n/a
n/a
Simple within Ecotect, Complex Standalone
n/a
Metrics on Workplanes. In-depth PDF documents
Diva
Easy, Fast w/ Rhino
Simple, but a lack of tooltips.
Simple
Full 3D & 2d Viewports & 3D images
Metrics on Workplanes In-depth PDF documents, False Colour Images.
methods available through animation tools within 3ds Max Imported data requires error checking, often large parts of the model needing to be redrawn or “traced” to fill missing surfaces. Newer versions of radiance not compatible with Ecotect. Radiance own interface is limited. Direct importation from SketchUp through plugins still in Beta stages. Manual Method requires experience with coding language Direct importation from plugins SketchUp still in Beta stages. Produces data that can be fed back into Ecotect to view the results effectively. Custom sky using direct horizontal irradiance can produces errors. Clear interface and comprehensive datasets from point in time calculations and climatic data.
Conclusion The aim of this paper was to evaluate tools available (currently used and new tools) to architects for the analysis of daylight design and performance of buildings. To this end firstly the state of daylighting analysis in architectural firms within Brisbane was surveyed, and secondly the ease of use of the daylighting analysis tools was assessed. This assessment included: comparing modelled point in time simulations against a real scenario (studio space), climate based modelling of the studio space with different tools and observation of issues related to the process of creating models, adapting models and implementing for analysis. The point in time illuminance calculations revealed that programs with common specific daylighting sky models that relate to realistic sky type lead to the most easily and realistic simulated results, furthermore, if the daylighting conditions can be recreated with direct and diffuse illuminance the results can be similar, however this leads to a variety of customizable options can easily confuse the user, which was seen with the use of Radiance and 3ds Max respectively. Radiance for indirect and direct were quite realistic, while 3ds Max for indirect results were realistic however, the direct component via the “Mr Sun” was difficult and produce inaccurate data without more specific data inputs. The simulations showed a direct correlation between the actual sky condition and the similar sky models used for analysis as seen in the Ecotect with Radiance and Rhino w/ Diva.
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Climate-based simulations revealed that, Rhino as a modelling platform with the DIVA lighting analysis plug-in gives the most comprehensive data set when calculating daylighting metrics, being based on Daysim, DIVA, like Daysim generates documents that contains comprehensive data on illuminance measurements and glare ratings. Daysim as a plug-in through Ecotect, unlike diva requires manual import to create visual data. However, while it is possible for 3ds Max/radiance software to easily produce point in time data, climate based analysis requires a much more time intensive method, by illuminance data input via spreadsheet data analysis. This same method can be done with radiance, however the advantage of Daysim, Diva and Ecotect, is that the same can be achieved in a much simpler way through their respective interfaces. The most adaptable method for daylighting analysis within architectural practice at this point in time, is using programs what integrate effectively with current BIM based or modelling solutions, and as seen in the poll the majority of firms report modelling with either Revit (BIM based) or SketchUp. Integration with Revit workflow is possible and efficient using Ecotect with the appropriate lighting analysis software (Radiance and daysim), while integration with SketchUp, is not as efficient, as a more manual approach is required due to the scripting based plug-ins. These methods aren’t exactly architect friendly as advanced background in IT or scripting is required. Unless the users are looking to invest in either Ecotect, 3ds Max or Rhino w/ Diva. New programs are steadily being developed; existing plug-ins will likely be improved reducing the need to additional software. Incompatibility between software is leading unknowing users to make design decisions on the assumption that these incompatibles are resolved within the software, and the results are correct. However this study has shown, they could be incorrect. More help features concerning input data, and simpler methods for creating analysis grids should help solve these problems as well as the expansion of what file types are supported for analysis. With the advancement of BIM and other analysis software packages such as DIVA and the upcoming Vasari, the software as well as plug-in compatibility should improve and enable architects to use the latest metrics within their analysis for daylighting. The study findings agree with previous studies in that current lighting software isn’t “architect friendly” (Attia et al., 2009). The processes and methods discussed within the paper reveals that some software could be more easily integrated into the current workflow of an architect than others. Although the process for daylighting analysis of 3d models using third party solutions is improving, to obtain more reliable results the user may need to purchase additional modelling software so they can gain access to the desired analysis software (i.e. Rhino and Diva). This issue may be resolved via the use of plugins, however, they are bounded by scripting and algorithms and can be troublesome for architects. Finally, the development of a method that can facilitate the understanding of how the data is processed could give architects an understanding of what a realistic result should look like. Ultimately giving architects the ability to overcome these shortcomings enabling them to use these complex metrics to benefit their design process and producing better outcomes for their clients, environment, profession and industry.
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REFERENCES: 1. ATTIA, S., BELTRAN, L., DE HERDE, A. & HENSEN, J. 2009. "Architect Friendly": A Comparison of Ten Different Building Performance Simulation Tools. IBPSA. Glasgow, Scotland. 2. AUSTRALIAN BUILDING CODES BOARD 2011. National Construction Code series 2011, Canberra, ABCB. 3. BRE GLOBAL LTD 2011. BREEAM 2011 New Construction Technical Guide. BRE Global Ltd,. 4. GREEN BUILDING COUNCIL OF AUSTRALIA 2008. Green star office design & office as built: technical manual, Sydney, Green Building Council of Australia. 5. GALASIU, A. D., & REINHART, C. F. 2008. Current daylighting design practice: Building Research & Information, 36(2), 159–174. 6. LEE, K., CHIN, S. & KIM, J. 2003. A Core System for Design Information Management Using Industry Foundation Classes. Computer-Aided Civil and Infrastructure Engineering, 18, 286-298. 7. LEE, Y. S. & GUERIN, D. A. 2010. Indoor environmental quality differences between office types in LEED-certified buildings in the US. Building and Environment, 45, 11041112. 8. MARDALJEVIC, J. 2001. The BRE-IDMP dataset: a new benchmark for the validation of illuminance prediction techniques. Lighting Research and Technology, 33, 117-136. 9. MARDALJEVIC, J. 2011. Opinion: Daylighting prescriptions: Keep taking the pills? Lighting Research & Technology, 43, 142-142. 10. MOON, P., SPENCER, D. E. 1942. Illumination from a non-uniform sky., New York, Illum. Eng. 11. NABIL, A. & MARDALJEVIC, J. 2006. Useful daylight illuminances: A replacement for daylight factors. Energy & Buildings, 38, 905-913. 12. REINHART, C. & BRETON, P.-F. 2009. Experimental Validation of Autodesk® 3ds Max® Design 2009 and Daysim 3.0. Leukos, 6, 7-35. 13. REINHART, C., LANDRY, MARION., BRETON, PIERRE-FELIX. 2009. Daylight Simulation in 3ds Max Design 2009 - Getting Started. Autodesk White Paper. 14. REINHART, C., MARDALJEVIC, J. & ROGERS, Z. 2006. Dynamic Daylight Performance Metrics for Sustainable Building Design. Leukos, 3, 7. 15. STANDARDS AUSTRALIA 2006. Interior and workplace lighting Part 1: General prinicples and recommendations. AS NZS 1680.1. 2006 ed. Sydney: Standards Australia,. 16. THOMPSON, J., DONN, M., OSBORNE, J. 2011. Variation of Green Building Ratings Due to Variances in Sky Definitions. Proceedings of Building Simulation 2011:12th
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Conference of International Building Performance Simulation Assoication. Sydney, 14-16 November.
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A Decision Making System for Selecting Sustainable Technologies for Retail Buildings Zainab Dangana1, Wei Pan2, Steve Goodhew3 Abstract The implementation of sustainable technologies can improve the energy and carbon efficiency of existing retail buildings. However, the selection of an appropriate sustainable technology is a complex task due to the large number of technological alternatives and decision criteria that need to be considered. Also, there exist series of uncertainties that are associated with the use of sustainable technologies, but have to be evaluated to achieve realistic and transparent results. The selection of sustainable technology is therefore most challenging. An earlier study was conducted with UK experienced practitioners including clients/developers, engineers, contractors and suppliers to identify the drivers and barriers for the use of sustainable technologies in UK retail construction. One major barrier identified from the study was the lack of a decision making tool, highlighted by both construction professionals and stakeholders in the retail industry. The large number of alternatives and potential solutions require a decision support method to be implemented. Information data on the economic variables, energy performance and impact on the environment of these systems is presently affected by vagueness and lack of knowledge. To deal with this high level of complexity and uncertainty an evaluation support approach is needed. This paper aims to develop a decision making framework to assist both retailers and construction professionals to define and evaluate the selection of sustainable technological options for delivering retail buildings. The research was carried out through a combination of a critical literature review and a survey-based study using expert opinions of retailers and contractors. The developed framework of decision criteria should provide a sustainable technology model to assist both construction professionals and stakeholders in the retail industry to systematically and effectively select the most appropriate technology. This approach should make the decision progression more transparent and facilitate sustainable development of retail buildings in achieving the carbon targets set by the UK and other governments.
1
Ph.D. Student; School of Architecture, Design and Environment; Plymouth University; Drake Circus, Plymouth, Devon, PL4 8AA;
[email protected]. 2 Associate Professor; Department of Civil Engineering, The University of Hong Kong, Hong Kong, China;
[email protected]. 3 Professor; School of Architecture, Design and Environment; Plymouth University; Drake Circus, Plymouth, Devon, PL4 8AA;
[email protected].
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Keywords: Sustainable retail construction, Low carbon retail buildings, Decision making criteria, Sustainable technology selection, United Kingdom.
1. Introduction Sustainability has become an increasing concern for the retail construction industry as construction activities have a significant impact on waste, energy use and greenhouse gas emissions (Ozorhon et al. 2011). Carbon emissions from energy use in non-domestic buildings account for around 18% of total emissions in the UK of which 18% is from retail (Carbon Trust 2009). A large number of new policies and regulations are being introduced to minimize the impact of the built environment and the construction industry on the environment, such as the ambitious targets set by the UK government to reduce carbon emissions by 80% by 2050 compared to 1990 levels (HMG 2010). These pressures are inducing a large amount of product and process innovations across the retail construction industry amongst manufacturers, suppliers, installers, clients, users, and many others. This has led to an increased interest in sustainable retail buildings, which has resulted in pressure to install sustainable technologies in buildings prior to the evaluation of their full life cycle implications. The study on which this paper reports is part of an on-going research project which aims to optimise the process, energy and carbon efficiency in retail construction by capitalising on sustainable technology. This research project addresses an overarching research question: "How can the use of energy and carbon be reduced for retail construction in a commercially viable way?" An exploratory study has been conducted with retailers and construction professionals in the retail construction industry (Dangana et al. 2012). The study reviewed the design and construction of sustainable buildings within the context of retail construction; identifying the drivers, barriers and opportunities for sustainable retail buildings and it explored how the UK mainstream retail sector is currently addressing the challenges related to sustainable retail buildings. The study identified the lack of a decision making system for the selection of appropriate sustainable technological innovations to optimize the process, energy and carbon efficiency for retail buildings. Currently, designers, constructors and retailers interested in adopting sustainable technologies in the retail construction industry have no comprehensive evaluation approach to review and select technologies. There is a demand for a systematic and effective evaluation tool for the selection of sustainable technologies (Pan et al. 2012, Devoudpour et al. 2012). The results indicate a big challenge for stakeholders in the retail construction industry to adopt implementation strategies that will support sustainable retail buildings overcoming the barriers for the slow uptake of sustainable technologies. The results are similar to a study conducted by Odhiambo (2010), which highlights that there is currently no comprehensive standard evaluation process to assist construction professionals to perform a holistic selection of a ST; with most studies addressed from a single issue perspective without taking into account other issues. The current evaluation approaches used by construction professionals for the selection of STs, such as financial
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models are inadequate as technology selection is a multi-criteria decision problem. Decision makers are unable to make selections due to lack of value-based decision criteria (Pan et al 2012), and also because some benefits of STs are easily measured (water, energy) while some are subjective, intangible or indirect such as improvements to productivity and health (Huang et al. 2011). Thus there is a great need for a methodology to assist decision makers to systematically select STs which addresses multiple criteria rather than from a single criteria approach to obtain an integrated decision making result (Wang et al. 2009). This holistic approach would allow the selection of STs relative to stakeholders’ objectives and consider the total influence on all systems (Belton and Stewart 2002). The aim of this present paper is to address the gap in knowledge of sustainable technology selection by proposing a conceptual decision making system to assist both retailers and construction professionals to define and evaluate the selection of sustainable technological options. The system is based on the concept of MCDA and sustainable development, in which the technologies can be analysed, evaluated and finally compared to select the optimal variant according to a set of criteria (Huang et al. 2011) based on the objectives of the stakeholders.
2. Literature Review “Sustainable technology” (ST) is defined as technology that provides for our current needs without sacrificing the future ability of populations to sustain themselves (Hmelo et al. 1995). Sustainable technology is not a new concept but is similar to the theory of “appropriate technology” (i.e. technology designed with special consideration for the environment, ethical, cultural, social and economic factors) that evolved in the1970’s, but has recently gained importance due to the increasing negative impacts of human activities on the planet and desire to promote sustainable development (Odhiambo et al. 2010). Sustainable building technologies include concepts and products that provide significant improvements in terms of the use of resources, harmful emissions, life-cycle costs and productivity, and building performance (Hakinenene at al. 2011). STs serve to contribute, support or advance sustainable development by reducing risk, enhancing cost effectiveness, improving process efficiency, and creating processes, products or services that are environmentally beneficial or benign, while benefiting humans (DuBose et al. 1995). Research conducted for the Intergovernmental Panel on Climate Change (IPCC 2007) estimates that around 30% of the baseline CO2 emissions in buildings projected for 2020 could be mitigated (avoided) in a cost-effective way globally, at no or even negative costs, if various sustainable technological options were introduced. Similarly, Carbon trust (2009) estimates that reducing the carbon emissions from the UK’s non-domestic buildings by 35% by 2020 could result in a net cost saving to the UK economy of more than £4.5 billion using simple and cost-effective building technologies that exist today. The use of sustainable technology emerges consistently as “one of the vehicles to enhance sustainability in the built environment” (Odhiambo et al. 2010) and is used as a strategy by construction professionals to design sustainable retail buildings.
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The selection of sustainable technologies is a complex and important task due to the rapid development of technologies, lack of skills and knowledge, uncertainties, risks, and a large number of technological alternatives and decision criteria that need to be considered (Pan et al. 2012, Wang 2009, Dangana et al. 2012). It can have significant implications on building performance and stakeholders’ satisfaction; creating long-term problems and hindering the adoption of such technologies. It is therefore necessary to base sustainable technology selection decisions on a clear understanding and a proper evaluation of the full range of implications associated with it. However, designers and clients face significant challenges in the selection of appropriate sustainable technologies due to certain characteristics of markets, technologies, and end-users which inhibit rational, energy-saving choices in the purchase and use of appliances as well as during the life-cycle of a building (HMG 2010, Dangana et al. 2012). Also, the risks associated with the reliability and effectiveness of new innovative products dissuades many professionals from specifying green or sustainable building materials (Pearce and Vanegas, 2002, Hakinene et al. 2011). This lack of enthusiasm may be attributable to clients’ risk aversity and the risk-averse culture of the construction industry (Pan et al. 2012). Currently, a Problematic selection approach is used in which many construction professionals choose to intuitively derive such decisions using their own perceptions of established professional experience. In such cases, the criteria evaluation process is very subjective and relies heavily on a manager’s experience and knowledge, as well as intuition (Wang et al. 2009). This has led to bias in the decision making process as it is based on limited issues and the influence on other systems of the building are not taken into account (Odhiambo et al. 2010). A systematic approach is needed for the retail construction industry to identify value-based criteria and establish their relative importance to achieve decision making objectives for the selection of sustainable technologies. The use of new efficient processes and knowledge of decision making phases can assist in the selection of STs (Hakinene et al. 2011), and also overcome the hindrances of using STs (Davoudpour et al 2012). Multi-Criteria Decision Analysis (MCDA) emerged as a formal methodology to support decisions in many fields and has been valuable in environmental decision making (Huang et al. 2011). MCDA is not a tool providing the “right” solution but an aid to decision making to assist stakeholders organize available information, consider the consequences and minimize the possibility of a post-decision disappointment (Belton and Stewart 2002). Wang (2009) describes MCDA as an operational evaluation and decision support approach suitable for addressing complex problems with high uncertainty, conflicting objectives, different forms of data and information, multi interests and perspectives in order to provide an integrated sustainability evaluation. The MCDA approach will be adapted and used to develop the conceptual framework for this study.
2.1 Decision making for selecting sustainable technologies Decision-making problems involve the process of searching or finding the course of actions from a given set of feasible alternatives which maximizes or satisfies certain criteria associated to the goals intended to be achieved (DCLG 2009). Decisions are made within a
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decision environment, which consists of the collection of information, alternatives, values and preferences available at the time when the decision must be made. Peldschus et al (2010) describes decision making as “a process involving activities that starts with recognition of a decision making problem and ends with recommendation for a decision”. The process can range from highly structured to highly unstructured decisions (Belton and Stewart, 2002) using either an alternative-focused or value-focused approach (Peldschus et al. 2010). One of the main goals in decision-making for sustainable retail buildings is to identify and choose the most sustainable technological option from among different alternatives. This complex decision problem usually involves a large number of stakeholders with multiple, often conflicting, objectives (Wang et al. 2009). The selection of sustainable technologies requires a highly structured, alternative-focused approach as the decision problem starts with a choice of options and involves the process of selecting a preferred option from multiple alternatives in a structured way. Techniques such as multi-criteria decision making methods support decision makers when faced with such a problem with a set of criteria on a set of alternatives. The adoption of multi-criteria methods helps to organise the decision-making process and usually includes four main stages: alternatives’ formulation and criteria selection, criteria weighting, evaluation, and final treatment and aggregation (Belton and Stewart 2002). There has been a significant use of multiple criteria decision analysis (MCDA) tools over the last two decades for environmental decisions (Wang et al. 2009, Huang et. al. 2011). MCDA has been successfully applied to solve evaluation problems in various fields such as sustainable energy, quality of service, engineering systems and new product development (Chen et al 2010, Pan et al 2012, Huang 2011). The evaluation and selection of building technologies has been widely studied, with most decisions based on knowledge-based techniques which take into account economic sustainability (Wang et al. 2009, Krisciunas et al. 2007). Multiple criteria approaches have been used by various authors for evaluating technical, environmental, social and economic aspects (Pan et al. 2012, Chen et al. 2010, Odhiamba et al. 2011). Sawers (1998) applied decision making matrices as a methodology for designers to compare design alternatives, considering both the objective economic traditional criteria as well as subjective factors such as competitive advantage, improved management information or strategic alignment. This approach does not identify project objectives but it illustrates how attributes can be structured into a value hierarchy where each attribute is weighted according to its importance relative to other attributes from the perspective of the stakeholders. Nassar et al. 2003 used multiple criteria for assessing construction methods but constrained the technical processes from the designers’ perspectives. Similarly, Nelms et al. (2005) presented a synthesis of classification systems that focused on the use of technical attributes of building systems and developed a comprehensive framework that incorporated a set of evaluation criteria that built on the work of other authors. Pan et al. (2012) developed a systematic approach for UK house building organizations to identify value based decision criteria and quantified their relative importance for assessing building technologies systematically.
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The proposed framework represents an integration and extension of these works and is developed to evaluate and select sustainable technologies from retailers and contractors perspectives for this study. The MCDA approach has been adapted for the development of the conceptual framework and comprises of three steps; problem identification and structuring; model building and use; and the development of action plans (Figure 1). The framework is intended to be holistic, to include the subjective qualities inherent in sustainable technologies and to reflect the retailers and constructors viewpoints as these have been perceived to be the main decision makers.
Figure 1: MCDA Approach (Adapted from Belton and Stewart 2002).
3. Methodology In this study, decision maker(s) or other stakeholders involved in the decision situation are those identifying the nature of the problem and driving the solution procedure towards the preferred direction. Although the two terms are sometimes used interchangeably, for our purposes, decision makers are those assigned with the responsibility to take the final decision, whereas stakeholders is a much broader notion encompassing any single individual or group of people with an interest or concern in the potential problem. When multiple stakeholders are involved in a decision problem, a common understanding of the problem should be achieved through the elicitation of ideas and the sharing of concerns and values. This phase of the study focused on the stakeholders directly involved in the decision problem in order to detect their preferences and values by engaging with those that actually influence the decision (retailers and construction professionals in the retail industry). Hence, the extracted values better reflect concerns and priorities of the people directly affected and were specific, measurable, agreed, realistic and time-dependent (DCLG 2009). The methodology adopted included a critical literature review and a study using expert opinions of retailers and contractors. Qualitative data was collected using a focus group and semi-structured interviews. The aim was to understand key issues that retail industry stakeholders are concerned with related to the selection of sustainable technologies. Faceto-face semi-structured interviews were carried out with ten senior managers from a leading UK retail contractor company in order to capture the points of view that decision-makers use as a frame for reference in their selection process. The focus group consisted of 12 participants (six retailers and six construction professionals) with experience in retail construction. The CAUSE (Criteria, Alternatives, Stakeholders, Uncertainty, and
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Environment) checklist was used to generate and capture ideas to identify the problem of why there was a slow up-take of sustainable technologies (Belton and Stewart 2002).
4. The proposed conceptual decision making system The conceptual decision making system utilises a set of criteria generated based on the results from the study. It presents a multiple criteria decision analysis problem and the MCDA approach will be adopted and recommended in solving the problem. The key steps of utilising the MCDA process are explained below.
4.1 Identify the problem This first step of the MCDA process is to identify the issue under consideration, to agree on the focus and the scope of the analysis, and to recognize external constraints such as physical or legislative environments, or time and resources available (DCLG 2009, Belton and Stewart 2002). The identification of the global goal would form the basis for structuring the problem systematically. The issue under consideration was, “The selection of appropriate sustainable technologies to optimize the process, energy and carbon efficiency for existing retail buildings” (Dangana et al. 2012).
4.2 Structure the problem This is a critical step for the subsequent analysis; it is often said that “a well-structured problem is a problem half solved” (Belton and Stewart 2002). The triangulation approach was used to ascertain whether the themes identified within the literature review were perceived to be the same by professionals working in the retail industry today; providing a more robust evidence basis for the argument (Bryman 2012). Based on the study, review and information from industry professionals, a combined list of 22 factors influencing the selection of sustainable technologies for retail buildings was produced. A preliminary coding exercise utilising Nvivo software was used and the 22 factors were grouped under the thematic headings of drivers, barriers and opportunities as illustrated in Figure 2. These factors provide the basis for structuring the problem and represent a fairly complete perspective of the user with regard to the problem. They can be used directly as criteria for evaluating and subsequently selecting the appropriate technology. The next stage involves model building to develop a framework for the evaluation of alternatives.
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Figure 2: Sustainable retail buildings
4.3 Build the model This is a dynamic process, both informed by and informing the problem structuring process and interacting with the process of evaluation (DCLG 2009). The type of model used depends on the nature of the investigation and the particular approach to be selected for analysis. The key elements for the model framework are based on the CAUSE framework; the alternatives to be evaluated; the model of values (criteria, objectives, goals) against which they will be evaluated; and how key stakeholders perspectives’ on the decision and uncertainties will be taken into account and modelled (Belton and Stewart 2002). A preliminary set of criteria was established by the researcher from the problem structuring phase (Table 1). Table 1: Preliminary Set of Criteria Reason
Criteria for selection of sustainable technologies. Focus on refurbishment & retrofitting of retail buildings (nondomestic buildings)
Technologies to focus on optimising process, energy and carbon efficiency for retail buildings.
•
It is estimated that by 2050 around 70% of the 2010 building stock will still be in use; it is very clear that low carbon retrofit would have a huge role to play in achieving carbon emission targets ( Carbon Trust 2009).
•
A leading UK contractor which is a good representation of the industry is involved in 95% refurbishment / retrofit projects and only 5% new build. This translates to a ratio of 19:1.
•
There has been much recent focus on measures to reduce the emissions from new retail buildings; the existing stock remains largely untouched (Dangana et al 2012).
•
Carbon emissions from energy use in non-domestic buildings account for around 18% of total emissions in the UK of which 18% is from retail (Carbon Trust, 2009). Significant cuts in emissions is essential as part of the UK’s commitment to reduce carbon emissions by at least 80% by 2050.
•
Energy costs are typically the second highest operating expense for a retailer, so implementing cost-effective energy saving strategies will have a direct and significant impact on profitability (ASHRAE Website).
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Early adopter and early majority technologies to be explored
•
A 10% decrease in energy costs has an equivalent impact on operating income as a 1.26% increase in sales for the average retail store (Energy Star website 2012)
•
The technology adoption lifecycle model describes the adoption or acceptance of a new product or innovation. The model indicates that the first group of people to use a new product is called "innovators," followed by "early adopters." Next come the early and late majority, and the last group to eventually adopt a product are called "laggards."
•
The capacity to innovate – or innovativeness – can lead firms to profitable outcomes, making significant contributions to the performance and efficiency of a business. Innovativeness in organizations can lead to competitive advantage and business performance.
4.4 Identification of alternatives and criteria to be evaluated This involves the identification of key factors which will form the basis of an evaluation. These are referred to as values, objectives, criteria, points of view (Belton and Stewart 2002). The term “criteria” will be used in this study and these are the measures of performance by which options can be judged. DCLG (2009) suggested two overall approaches for identifying decision criteria: bottom-up and top-down. The bottom-up method is used to identify criteria if options are already given by asking how the options differ from one another in ways that matter. The top-down method is used to identify criteria based on the overall objectives provided by asking about the aim, purpose, mission or overall objectives to be achieved (Pan 2006). In this study the top-down approach was more appropriate for the selection of sustainable technologies using the perspectives of a leading UK contractor and retailers. The study identified 22 criteria; these were clustered and grouped into several sets that relate to separate and distinguishable components of the overall objective. The main reasons for grouping criteria were: to ensure the set of criteria selected is appropriate to the problem; to ease the process of calculating criteria weights; to help organize the criteria and objectives; to facilitate the emergence of higher level views of the issue; and to highlight conflicts in objectives leading to refinement (DCLG 2009). The decision criteria at the first level clustered the criteria under the main stakeholders (retailers and contractors) who were perceived to play a key role in decision making for the selection of sustainable technologies. The criteria were then broken down into the second level with 10 broad criteria (Figure 3). The conceptual hierarchy presented will undergo a process of refinement, iteration and modification in the next phases of the study. The next step involves evaluation and exploration of alternatives to identify the options that contribute to the achievement of the decision objective. The alternatives may be relatively few and explicitly defined or from a large pool of alternatives as is the case in this decision problem.
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Figure 3: Value Tree of Criteria for Selection of Sustainable Technologies
5. Conclusions and future research The selection of sustainable technology is an important and complex task due to the rapid development of technologies, lack of skills and knowledge, uncertainties, risks, and a large number of technological alternatives and decision criteria that need to be considered. This can be classified as a complex multi-criteria decision problem due to the high number of alternatives, potential solutions and various stakeholders (clients, professional advisors, endusers) leading to the slow take-up of sustainable technologies. This paper has developed a decision making system to assist both retailers and construction professionals to define and evaluate the selection of sustainable technological options. This system involved a process of establishing decision criteria, which included clarifying the decision context, establishing decision objectives, identifying, clustering and assessing decision criteria. The study has generated a set of criteria against which sustainable technologies will be evaluated and compared in the next phase of the study. The matrix of criteria would be reviewed and evaluated every year to accommodate the changing needs of the stakeholders. The decision making system should provide a sustainable technology model to assist both construction professionals and stakeholders in the retail industry to systematically and effectively select the most appropriate technology. From a communication perspective the system will provide a means for all levels of decision-makers to share their concerns and findings. In addition, it will also help to promote dialogue amongst different stakeholders to foster appropriate risk allocation at the outset of the project or before use of the technology. This should make the decision progression more transparent and facilitate sustainable development of retail buildings in achieving the carbon targets set by the UK and other governments.
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Nevertheless, it is worth noting that although the aim of this paper is to develop a decision making framework to assist both retailers and construction professionals to define and evaluate sustainable technology selection for retail buildings, the decision making criteria were explored predominantly from the perspective of a main contractor and their clients and supply chains. There are other key stakeholders, such as architects, planning officers, endusers, which also play an important role in the selection of sustainable technologies. The decision criteria which these stakeholders use should also be explored and included in the decision making system, which will be studied in the next stage of the research.
References Belton V and Stewart T J (2002). Multi Criteria Decision Analysis - An integrated Approach. Kluwer Academic Publishers, Boston. Bryman A. (2012). Social Research Methods. 4th edn. Oxford University Press, Oxford. Carbon Trust (2009) Building the future today: transforming the economic and carbon performance of the buildings we work in. London: Carbon Trust. Chen Y, Okudan G and Riley D (2010) “Sustainable performance criteria for construction method selection in concrete buildings”. Automation in construction, 19 (2): 235-44 Dangana Z, Pan W and Goodhew S (2012) “Delivering sustainable buildings in retail construction” In: Smith, S.D. (Ed) Procs 28th Annual ARCOM Conference, Edinburgh, UK Davoudpour H, Rezaee S and Ashra M (2012) “Developing a framework for renewable technology portfolio selection: A case study at a R&D center”. Renewable and Sustainable Energy Reviews 16 :4291– 4297 DCLG (2009) Multi-Criteria Analysis: a Manual, London. DuBose J, Pearce A and Vanegas J (1995) “Sustainable technologies for the building construction industry”. In Proceedings of the Designing for the Global Environment Conference. November 2-3, 1995, Atlanta, GA. Energy Star (2012) Energy star for retail, (available http://www.energystar.gov/index.cfm?c=retail.bus_retail [accessed on 22/10/2012])
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ASHRAE (2011) Advanced Energy Design Guide for Medium to Big Box Retail Buildings, (available online www.ashrae.org/freeaedg [accessed on 10/10/2012]) Huang I B, Keisler J and Linkov I (2011) “Multi-criteria decision analysis in environmental sciences: Ten years of applications and trends”. Sci Total Environ 409: 3578-3594 Hakkinen T. and Belloni, K (2011), “Barriers and drivers for sustainable building”, Building Research and Information, 39(3): 239-255.
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Hmelo et al (1995) “A problem-based course in sustainable technology”, Proceeding FIE '95 Proceedings of the Frontiers in Education Conference, on 1995. HM Government (2010) Low carbon construction, innovation & growth team. London: BIS IPCC (2007) Summary for Policymakers. In: Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Krisciunas K, & Greblikaite J (2007). “Entrepreneurship in Sustainable Development: Sees Innovativeness in Lithuania”. Inzinerine Ekonomika-Engineering Economics (4): 20-26. Nassar K, Thabet W and Beliveau Y (2003) “A procedure for multi-criteria selection of building assemblies.” Automation in Construction, 12 (5): 543-60 Nelms C, Russell A D and Lence B J (2005) “Assessing the performance of sustainable technologies for building projects”. Canadian Journal of Civil Engineers, 32: 114-128 Odhiambo, J and Wekesa, B (2010) “A framework for assessing building technologies for marginalised communities”, Human settlements Review, Volume 1, Number 1. Ozorhon B, Abbott C and Aouad G (2011) “Design, Process, and Service Innovations to achieve sustainability”. Management and Innovation for a Sustainable Built Environment, 20 – 23 June 2011, Amsterdam, The Netherlands Pan, W., Dainty, A.R.J. and Gibb, A.G.F. (2012) Establishing and Weighting Decision Criteria for Building System Selection in Housing Construction. ASCE Journal of Construction Engineering and Management, 138(11), 1239-1250. Pan W (2006) “A Decision Support Tool for Optimising the Use of Offsite Technologies in House building, PhD Thesis, Loughborough University, UK. Pearce, A. R. and Vanegas, J. A. (2002) “A parametric review of the built environment sustainability literature”. International Journal Environmental Technology and Management, 2 (1/2/3), 54–93. Peldschus F, Zavadskas E K, Turskis Z, & Tamosaitiene J (2010). “Sustainable assessment of construction site by applying game theory”. Inzinerine Ekonomika-Engineering Economics, 21(3): 223-236 Sawers J (1998) “Effective evaluation of green technologies” Proceedings of the Green Building Challenge, Dublin, Ireland. Wang J.J, Jing Y.Y, Zhang C.F et al (2009) “Review on multi-criteria decision analysis aid in sustainable energy decision-making”. Renew Sust Energ Rev 13:2263–2278
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An Evidence Based Online Design Platform: Challenges and Limitations Marina Di Guida 1, Judit Kimpian2, Paola Marrone3, Lucia Martincigh4, Dejan Mumovic5, Craig Robertson6 Abstract Historically, the problems associated with feedback in building energy consumption are threefold: a) a lack of information, b) a lack of effective use of the existing data, c) a lack of knowledge how to engage more than the interested few to understand and act on building performance. Whilst introduction of Display Energy Certificates (DECs) created a framework for information generation, their intended role is to place the subject building within the context of similar type of buildings but this data can provide little or no insight into the root causes of the energy performance. To go beyond the headline benchmarking of energy performance of buildings and to provide evidence based design advice to various stakeholders such as building designers, clients/investors, facility managers, and users on how their buildings are performing with regard to their architectural, engineering and occupancy characteristics we need an intelligent and rapid feedback tools/protocols. It is well known that the useful feedback should contain extensive building design and performance data, benchmarked against similar type of buildings, and accompanied with ‘do and do not’ reflections from all key stakeholders involved especially the design team and facilities managers. In order to facilitate the need for more comprehensive feedback in the UK, a consortium of researchers from industry and academia has created an online Evidence Based Design platform called CarbonBuzz. Having this in mind this paper describes the development of an Italian Evidence Based Design online platform using the UK based CarbonBuzz as an example. The paper is set out in 3 sections: a) a framework for platform development, analysing the source of data and completeness of records currently in CarbonBuzz in order to inform the development of the Italian platform and b) a data structure review, identifying potential challenges in translating 1
PhD Student; Dipartimento di Architetturra; Università Roma Tre; Piazza della Repubblica, 10-00185 Roma, Italy;
[email protected]. 2 Director of Sustainable Architecture & Research; Aedas R&D; 5-8 Hardwick St-London EC1R 4RG United Kingdom;
[email protected]. 3 Associate Professor; Dipartimento di Architetturra; Università Roma Tre; Piazza della Repubblica, 10-00185 Roma, Italy;
[email protected]. 4 Associate Professor; Dipartimento di Architetturra; Università Roma Tre; Piazza della Repubblica, 10-00185 Roma, Italy;
[email protected]. 5 Associate Professor; University College of London (UCL), Faculty of Built Environment, Bartlett School of Graduate Studies; 14 Upper Woburn Place-WC1H 0NN London, United Kingdom;
[email protected]. 6 PhD Student; University College of London (UCL), Faculty of Built Environment, Bartlett School of Graduate Studies; 14 Upper Woburn Place-WC1H 0NN London, United Kingdom;
[email protected].
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the UK data structure in the context of Italian regulatory requirements, and c) developing prototype, describing the data collection protocol used to inform the development of the Italian platform which follows Evidence Based Design principles with an aim to provide advice on how choices related to design, construction and management of a building impact its carbon emission. The paper concludes by reflecting on these limitations of this development programme and describes some additional features employed by the Italian platform in order to overcome some of these challenges. Keywords: energy performance, low-carbon design, web platform, post-occupancy evaluation, occupant feedback
1. Introduction Previous research studies clearly showed that ongoing efforts to deliver low carbon buildings while providing acceptable indoor environmental quality have had little success (Dasgupta et al 2011). The absence of readily available energy use data matched with descriptors for physical forms, indoor environment characteristics, occupant use of space and behaviour affects the accuracy of predicted energy consumption at the design stage and prevents the development of transparent and validated strategy for modelling energy use in buildings. (Prodromou et al 2009). This has been further substantiated by the opinion of 286 UK professionals regarding designing of low carbon buildings, which has clearly identified the inability to predict the actual consumption of buildings as one of the key risks (Dasgupta et al 2011). The discrepancies between operational versus designed performance of buildings have been additionally substantiated by Post Occupancy Evaluation studies (POEs) and as a result the designers and engineers are increasingly under pressure to provide more accurate estimates for energy consumption in buildings and supply guidance to achieve carbon reduction targets. Although essential, the detailed POEs are usually carried out by the interested few in academia and industry, on a small number of buildings involving expensive and time consuming monitoring campaigns, all of which is limiting the possibility to formulate robust Evidence Based Design guidance. Moreover, data collected is rarely collated in a single database and disseminated to inform further research.
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To overcome these limitations a number of institutions have embarked on research programmes including: the Building Energy End-Use Study in New Zealand (www.branz.co.nz/BEES); the Energy Efficient Buildings Research programme by the Precourt Energy Efficiency Center at Stanford University in the USA
(http://peec.stanford.edu/buildings/); and a retrofit specific programme in Canada at the Institute for Building Efficiency (http://www.institutebe.com). In the UK, a consortium of partners led by Aedas R&D and supported by the Chartered Institute of Building Services Engineers (CIBSE), the Building Research Establishment (BRE), the Royal Institute of British Architects (RIBA), University College London (UCL) and AECOM, along with other industry partners, has developed an Evidence Based Design online platform – CarbonBuzz (www.carbonbuzz.org). Initially funded under University College London (UCL) UrbanBuzz Programme, CarbonBuzz is a free platform that collects anonymous energy building consumption data to highlight the performance gap between design figures and actual readings of recent projects (Figure 1). Figure 1: Overview of CarbonBuzz It is believed that this crowdsourcing data platform would enable researchers and building professionals to map and benchmark the annual energy consumption of a building from design to operation by fuel as well as by energy end uses. In doing so it highlights the gap between design stage predictions and operational energy use and draws attention to ‘unregulated’ energy use which have a significant impact on achieving expected energy performance (Figure 2).
Figure 2: CarbonBuzz – mandatory compliance vs. actual performance Unlike the UK Climate Change Act (2008) which has committed the UK Government to cut the CO2eq emission by 80% by 2080, the Italian Government adopted lesser carbon reduction targets based on the revised EU Energy Performance of Buildings Directive (EU/31/2010) Strategy 20-20-20 which requires each Member State to reduce CO2eq emissions and the consumption of primary energy by 20% (from 1990 level), and to increase the use of renewable energy supply by 20% by 2020. Within the European Action Plan for
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Energy Efficiency, Italy requires benchmarking tools and methods that use actual consumption to verify theoretical estimations. Updating of the legislative framework in Italy (D.Lgs 2005/92, D.Lgs 2006/311, D.Lgs 2008/115, DPR 2009/59, D.Lgs 2011/28) as well as the technical norms (UNI-TS 11300) that introduced standards, methodologies and innovative tools for new construction and refurbishment of public buildings, further action is required to sustain the interventions in this sector. Having this in mind this paper aims to: a) analyse the source of data, completeness of records currently in CarbonBuzz in order to inform the development of Italian Evidence Based Design online platform and b) identify potential challenges in translating the UK data structure in the context of Italian regulatory requirements, and c) describe the data collection protocol used to inform the development of the Italian platform which follows Evidence Based Design principles with an aim to provide advice on how choices related to design, construction and management of a building impact its carbon emission.
2. Framework for Platform Development To define a framework for the development of Italian platform, a simple statistical analysis was carried out to identify a) type of registered organisations, b) type of registered organisations uploading the energy data, c) type of registered organisations uploading design and actual data, d) number of projects with energy data by building type, and e) completeness of data records. This analysis provides an insight who might be the most interested stakeholders and potential supporters of the Italian platform. Analysis of CarbonBuzz database shows that the platform had 575 registered users in July 2012, an increase of 42% from 2011 (July 2011- July 2012), across 17 company categories. [Since the time of this analysis the number of registered organisations increased to 674 to November 2012]. The major groups registered: architects (141 architectural practices registered; 23% increase), engineers (82 engineering practices registered; 21% increase) and consultants (59 consultancies registered; 51% increase). An 80% increase in University registrations has to be noted (74 universities registered) which means that 25% of all UK Higher Education Institutions (universities, colleges of higher education and further education colleges that offer HE courses) have been registered with CarbonBuzz (includes university estates as well as research groups). Other organisations include: business management (43), central government (7), computing companies (16), construction (23), local government (14), manufacturers (12), media (2), property management companies (22), quasi-governmental (19) and surveyors (3).
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Table 1: Registered organisations contributing energy data
Company Categories
Number of Organisations Contributing Energy Data 2011
Number of Organisations Contributing Energy Data 2012
% Change
Quasi-governmental
8
23
188
Architects
82
100
22
Engineers
18
11
-39
University
2
2
0
Consultants
1
1
0
Business management
4
16
300
Local government
3
1
-67
Total
121
159
31
The overall number of organisation contributing design and actual data has not increased to the same degree as the total number of organisations registered with CarbonBuzz (Table 2). There has been an overall increase of 7%. Consistent with the makeup of the registered organisations and the 2011 data, architects still contribute the highest number of energy records (18 new projects). Table 1 shows large percentage increases in contributions from quasi-Governmental organisations (15 new projects) and Business Management (12 new projects) organisations albeit from a very low base. Note that the reduction in numbers is due to project deletions throughout the analysis period. Table 2: Organisations contributing design and actual data Company Categories
Number of Projects 2011
Number of Projects 2012
% Change
Architects
25
16
-36
Engineers
6
6
0
Business management
4
7
75
University
0
1
100
Quasi-governmental Property
8 2
15 0
88 -100
Total
43
46
7
Table 3 shows that the number of projects with energy data in the database has increased from 299 in 2011 to 381 in 2012, this decreases to 319 if those marked as test are not included in the count. Education is the largest category contributing 42% of the total non-test buildings. 243 (76% of the total) of non-test projects have any energy data (either design or actual electricity or heat consumption data) of these 49 (15% of the non-test projects) have design and actual electricity data and 44 (14%) have design and actual heat consumption data. In total 40 non-test projects (12.5%) have design and actual electricity and heat consumption data for comparison in the database.
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Table 3. Projects with energy data by CarbonBuzz sector Sector
Number of Projects
Number of Projects (not including those marked 'Test')
Percentage of total (non-Test)
Civic & Community
11
11
3
Office
110
85
27
Education
151
135
42
Health
16
12
4
Residential
37
28
9
Retail
21
18
6
Sport & Leisure
20
19
6
Hospitality
6
5
2
Industrial
4
3
1
Other
5
3
1
Total
381
319
100
Of all the projects 96% (306 projects) have a gross floor area figure and 82% (262 projects) have project value associated with the project. However basic building geometry factors are less well represented; circa 15% of projects have a data entry for actual number of storeys and less than 10% have a figure for actual floor to floor height. Less than 50% of projects have figures for actual numbers of occupants and operating hours and almost no projects have detail on facility management arrangements. Analysis of the data base has identified five types of data entry error: a) format errors, b) unit errors, c) boundary errors, d) category errors, and e) errors with a drop down classification. Most of the above errors can be omitted in the Italian platform through user guidance, adjustment to drop down menus or relational checks being built into the database.
3. Data-structure Review CarbonBuzz is based on the data structure of the Display Energy Certification (DEC) system, set up as part of the UK’s implementation of the EU Energy Performance of Building Directive (EPBD) since 2006. This certification rates operational performance – and the CarbonBuzz tool takes lessons learned from benchmarking actual energy use and applies them to inform design phase predictions. The procedures for a National Calculation Methodology (NCM) for the purposes of production of Energy Performance Certificates (EPC – asset rating) and Display Energy Certificates (DECs – operational rating) are incorporated in software tools developed by the UK Government (SBEM – non domestic and SAP – domestic buildings), however other approved Dynamic Simulation Models (DSM) can be used (IES, TAS, Design Builder). This approach is used for demonstrating compliance with Part L2a of the UK Building Regulations (HM Government 2010). CIBSE TM22 Energy Assessment and Reporting Methodology (CIBSE 2012) data structure represents the foundation of the DEC system and allows for the collection of building information in very general terms from the ‘top down’, or for users to build up very detailed illustrations of data use from individual loads from the ‘bottom up’. The aim of using TM22 as a basis for
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collection is in order to provide cross industry coordination and take advantage of data that may already be collected elsewhere. The current published CarbonBuzz database is split into two subsets: ‘Project Details and ‘Energy Records’. For a detailed structure of this complex database please register as the CarbonBuzz user. Project Details describe the characteristics of the building and are in turn broken down into: •
Project Details (per project) detailing: building location, building use, number of zones, building ownership and tenancy, design/management teams;
•
Project Details (per energy record) detailing: data collection dates, if data comes from a particular data set (i.e. TSB BPE or DEC data), benchmark targets/rating system used, which edition of building regulations applied, embodied energy, any uploaded drawings or images, cost;
•
Project Details (per zone) detailing: servicing strategies (lighting, heating, ac, nat. vent etc.), low and zero carbon technologies employed, building fabric details (proportions of glazing, U-values etc.), air tightness, building dimensions, separable or special energy uses, occupancy rates, facilities management strategies.
Energy Records describe the energy consumption associated with the building and are split into Design and Actual data. Each contains: •
Source of data (software if prediction, meter type/frequency if actual);
•
Total Electrical Energy use broken down into: Low and zero carbon uses/sources, Building loads (services, lighting), Occupational loads (small power, ICT, catering transport, special or separable functions);
•
Total Non-Electrical Energy use broken down into: Low and zero carbon uses/sources, Building loads (services, heating, DHW), Occupant Loads (catering).
Unlike the UK where users can compare design stage carbon emissions, calculated during the planning and detail design phases against the DEC benchmarks, calculated in kg CO2/m2/year (kWh/m2/year), in Italy the legal limits have been set based on an Energy Performance Index (EPi limit) that is evaluated in kWh/m²/year (for residential buildings) and kWh/m3/year (for non-residential buildings) which deals with winter heating performance only. The Italian Guidelines for Energy Classification of Buildings (D.M. 26/06/2009) prescribes that the energy class of a building, EPgl (index of global energy performance), is calculated using the following equation (Bianchi et al 2009): EPgl= EPi + EPacs+ EPe + Epill,
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where: EPi: index of energy performance for heating, EPacs: index of energy performance for the production of hot water, EPe: index of energy performance for cooling, and EPill: index of energy performance for artificial lighting. At the moment, the energy class for a building is still determined by the performance index for winter heating (EPi) and hot water production only (EPacs) (Romani et al 2011). For summer cooling, only a qualitative assessment of the building envelope characteristics is required (Boffa et al 2012). The EPi index has to be lower than the minimum fixed value defined by the following parameters; a) heating degree-days for selected climatic zone, and b) surface (external building envelope area) to volume (building volume heated) ratio (S/V). Some regions, in anticipation of the long delayed national guidelines, have developed their own procedures on minimum requirements and the certification of buildings. The Italian platform will incorporate the definition of the minimum requirements and methodologies for the assessment of the cooling energy performance (EPe), also for artificial lighting (EPill), and the regulations on the use of renewable energy technologies in buildings (EU 2008). Furthermore, the following issues have led to a modification and development of new datafields in the Italian data structure: a) modus costruendi (heavy weight continuously supported structure vs. light weight wood/steel frame structure), b) lack of ‘cradle to gate’ embodied carbon data in Italy: some research has been carried out in this field including the so-called “Accordo di Programma” between the Region Marche and ITACA, l’ITC-CNR and the Polytechnic University of Marche which developed the first institutional database of building materials and products, which follow the CEN TC350 life-cycle analysis methodology developed by the EU, c) a large variety of the environmental sustainability protocols used which are used only in two Italian regions (ITACA Protocol, BREEAM, LEED Italia, CasaClima, Passivhaus), d) lack of regulatory requirements to develop a detailed submetering strategy to quantify energy end uses such as heating, cooling, lighting, small power loads, etc. Figure 3 compares the structure of both British and Italian online platforms.
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Figure 3: British vs. Italian database structure
4. Developing Prototype: Data Collection Study For energy performance feedback to be informative it needs to capture both building design and performance data. Buildings can then be benchmarked against similar typologies and
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‘do and do not’ reflections can be added by key stakeholders involved especially the design team and facilities managers. A data collection study was carried out in Rome to identify potential problems in translating CarbonBuzz data structure to the Italian regulatory environment and practice. The work was structured around five key phases:
4.1 Selection of case study buildings Six buildings were selected to cover a range of ages, building types and building systems. The buildings were listed in three major groups: a) buildings using non-electrical energy sources for heating with no cooling systems or mechanical ventilation (1 case study), b) buildings using non-electrical energy sources for heating with electrical cooling and mechanical ventilation (3 case studies), and c) buildings using electricity both for heating and for cooling (heat pump) or mechanical ventilation (2 case studies).
4.2 Data Collection The data gathered from the Roma Tre University Estates included the following: a) architectural and morphological parameters (location, orientation, year of construction, heated building volume, usable floor area, building envelope area, S/V ratio, number of floors, floor to ceiling height), b) use of buildings (academic department, number of occupants, office hours, and system operating hours), c) building construction parameters (building envelope characteristics, glazing parameters, etc), d) building services data (heating, cooling, mechanical ventilation, etc.), e) facilities management (energy data, review of energy certificates, interviews with energy managers).
4.3 Inspection of the sample buildings As part of the data collection the team carried out a series of site visits to verify the information obtained from the desktop study. At this stage further data was collected about mechanical systems via questionnaires aimed at facilities managers. These covered energy consumption patterns and contributing factors including the use of electrical devices, artificial and natural lighting, heating/cooling installations, natural and artificial ventilation.
4.4 Collection of electricity consumption data Apart from the data obtained from the energy performance certificates the following data was acquired from the energy managers: a) monthly electricity bills and b) half-hourly electricity data for a full year for all the buildings in the pilot. Half hourly electricity data shown in Figure 4 were used in to highlight the limitations of the Italian EPi calculations which according to 2008 implementation of EPBD excluded both EPe: index of energy performance for cooling, and EPill: index of energy performance for artificial lighting.
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Figure 4: Electrical consumption – naturally ventilated heavyweight building vs. lightweight building with mechanical cooling (half hourly data)
4.5 Non-electric energy consumption Figure 5 provides the headline energy consumption results obtained from the POEs carried out in 6 case studies. Energy end uses estimated in this way were uploaded into the platform, where it is possible to read either by project or by portfolio. In this figure and for each case study, electrical and non-electric energy consumption refer to envelope’s characteristics (form coefficient S/V represents the ratio between dispersing area and heated volume of the building), structural type (massive building/concrete frame), presence and types of plant systems (heating, cooling, mechanical ventilation).
Figure 5 : Overview of energy consumption in 6 case study buildings Table 4 compares EPi values, which were adjusted to take into account the equipment’s intermittence, the building’s structural inertia and the equipment’s operating hours, with the actual energy consumption and EPi lim values. For the buildings that have non-electric heating, table 4 compares Epi values (energy performance index) – which derive from energy certificates and were re-evaluated by considering a correction factor due to intermittency of the equipment (which is calculated on
130
inertia of the building and operating hours) - with actual energy consumption derived from non-electric bills; both values were compared with the limit values of energy performance (Epi lim), established by law: in almost all cases the real consumption and the consumptions in the energy certificates were higher than the limit value, but surely the real ones were closer. Table 4: Actual vs. estimated energy consumption data for 4 case studies (with nonelectric heating) case study
EPi 3 [kWh/m /y]
energy class
intermittent factor
revalued EPi 3 [kWh/m /y]
nonelectric consump. [kWh]
Heated volume 3 [m ]
non-electric consump. 3 [kWh/m /y]
EPi lim 3 [kWh/m /y]
2
30,89
G
0,6136
18,95
1073337
84476
12,71
7,86
3
31,03
G
0,7994
24,81
119203
17625
6,76
6,89
4
21,46
F
0,6136
13,17
625526
78169
8,00
6,61
5
35,50
G
0,6136
21,79
464198
51645
8,99
6,56
5. Conclusions This Italian-UK collaborative research project has reinforced the need for more transparency in reporting energy consumption data to address the lack of evidence and clarity about building performance. It is clear from this study that this data is difficult to get hold of and compare ‘like for like’ even across a region where this is mandated. Although the CarbonBuzz has been created to address this problem, a brief analysis of the source and quality of data currently in CarbonBuzz demonstrates that the data available in the public domain is still not sufficient to support the development of an alternative approach (Hawkins et al 2012) for understanding the impact of building design parameters on the energy use in buildings. This is reflected in the fact that only 8% of 575 registered users have contributed both design and actual data. However, the fact that there is a steady increase of architectural, engineering practices using the platform indicates that there is an appetite for this approach. Indeed, the next UK release of the platform has built on feedback from a broad range of stakeholders to incorporate additional functionality to manage and share such data transparently over time and to improve the capture of physical forms, indoor environment characteristics and occupant use of space and behaviour. The Italian prototype has adopted what were perceived as the strong points of the CarbonBuzz approach including the following principles: a) data structure facilities creation of a database divided into categories where data about CO2 emissions can be collected and compared like for like, b) facilitating comparison between energy certification and operational energy use (adapted to Italian regulatory context), c) analysis of end use energy consumption, and d) ease of use and accessibility for all users, online sharing of data relating to consumption. The data collection and processing pilot study carried out on 6 university buildings has highlighted how hard it was to get evidence and clarity about
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building performance even for new buildings. Capturing project and energy use data from Italian case studies has identified some potential limitations of using the UK CarbonBuzz platform on international projects. These limitations arose from the type of data available, differences in the implementation of EPBD regulations and Italian building types and construction systems. The data collection and processing study provided a very useful insight which has been used to develop a prototype for an Italian online platform which will be presented at the CIB 2013. Further data fields have been inserted into the platform with regard to the following: a) building envelope and its exposure and occupancy to enable implementation of Italian EPBD protocols. This paper underlined some critical features, together with the necessity of future actions aiming on the one hand to the fine tuning of the system of systematic survey of data and of their informatics management, on the other to the environmental mitigation and infrastructural updating for the energy efficiency of the examined buildings.
References Bianchi F, Altomonte M, Cannata M E, Fasano G (2009) Definizione degli indici e livelli di fabbisogno dei vari centri di consumo energetico degli edifici adibiti a scuole - consumi energetici delle scuole primarie e secondarie, Edizioni ENEA. Burman E, Kimpian J, Mumovic D. (2012) “Performance Gap & Thermal modelling: A Comparison of Simulation Results and Actual Energy Performance for an Academy in North West England”, Proceedings of the 1st International Building Performance Simulation Association England Conference, September 2012, Loughborough University, Loughborough, UK. CIBSE (2006) TM22 Energy Assessment and Reporting Methodology, CIBSE, UK. Dasgupta A, Mumovic D, Prodromou A (2011) “Operational vs. Designed Performance of Low Carbon Schools in England: Bridging a Credibility Gap.” ASHRAE HVAC & Research Journal 1-2: 37-50. EU (2008) Implementation of the Energy Performance of Buildings Directive: Country Reports 2008, EU Commission. Hawkins D, Hong SM, Raslan S, Mumovic D, Hanna S (2012) “Determinants of Energy Use in UK Higher Education Buildings Using Statistical and Artificial Neural Network Methods.” The International Journal of Sustainable Building Environments 1: 24-33. HM Government (2010) The Building Regulations 2000 - Approved Document L2A (2010) Conservation of fuel and power in new buildings other than dwellings (available online). Prodromou A, Dasgupta A, Mumovic D (2009) Consultation on the School Carbon Management Plan: UCL Evidence, Accompanying Evidence Document, CIBSE Knowledge Bank, London
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Non-residential building energy use today and tomorrow Andrew Pollard1, Michael Babylon2 Abstract The six-year long Building Energy End-use Study (BEES) has collected detailed information on energy use for over 120 non-residential premises throughout New Zealand. Major energy end-uses such as lighting and fixed wired appliances were measured by electrical energy measurements at the relevant circuit boards within the premise at one minute intervals. If present in the building, shared services such as lifts and HVAC systems were also monitored. Measurements were also made of selected individual plug-in electrical appliances by attaching specialised monitoring equipment to them. Additional information about the environment within the premise such as the temperature, humidity, luminance levels and CO2 levels were also collected at a 10-minute interval. The monitoring period was typically over a two week period. The energy use data from BEES provides a unique nationwide dataset. This paper discusses some of the characteristics of the observed energy use and possible pathways to improve the energy use in non-residential buildings. One important application for such a dataset is to provide realistic equipment usage patterns as inputs into computer-based building simulation models. These improved models will allow future building performance to be better predicted and will allow the impacts of changes to buildings and their operation to be better understood. Keywords: Non-residential Energy Use, Energy End-Use, Building Energy Simulation, Computer Use, Appliance Use.
1. Non-residential buildings The Building Energy End-use Study (BEES) is a study to better understand energy use in New Zealand’s non-residential buildings. Defining what a non-residential building is itself a complicated question let along determining its energy use. There is no database of New Zealand’s non-residential buildings so a sample frame has to be constructed using a particular methodology. For BEES, a database of valuation records of legal titles was used (Camilleri and Isaacs, 2010). This database includes in addition to the rateable valuation information, a legal title and a usage category.
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Building Physicist, BRANZ, Judgeford, Porirua, New Zealand.
[email protected]. Building Physicist, BRANZ, Private Bag 50908, Judgeford, Porirua, New Zealand.
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The legal title identifies either; a land parcel, one or more buildings, parts of a building (for example, each floor of a multi-level building may have a separate title), or another nonoccupied structure. The activities within a building determine whether it is non-residential and the building category, e.g. commercial office or retail. Categorising the usage of a building can be involved. There can be a variety of activities undertaken within the building and multiple classifications may be required. This can include situations where there is a mixture of nonresidential and residential uses such as apartments within the same building as retail businesses or offices. There are also more changes of tenancy within non-residential buildings than is the case for residential buildings. This can change the types of activities within in the building as well as result in varying proportions of floor area which is vacant. Educational and health buildings have characteristics that typically make them distinct from other non-residential buildings. Commonly these types of buildings occur in clusters of buildings as part of a campus which may or may not have shared services between the buildings. For this and other reasons, educational and health buildings were excluded from the BEES sample frame (see Isaacs et al, 2009 and Isaacs et al, 2010).
2. Energy use in non-residential buildings The varied tenancy in non-residential buildings can make collection of data on energy use complicated, as multiple energy accounts may be involved. BEES found that less than 9% of premises occupied all floors within their building (Saville-Smith and Fraser, 2012). In addition to the energy use of each of the tenanted areas within a building, there is also a base building energy use. Base building energy use is the energy used by non-tenanted activities and includes energy use for shared areas (lighting) and any HVAC plant, lifts or other services. As a premise gets bigger, it would be expected that its premise energy use would also increase, as more areas may require more lighting, computers, office equipment, appliances and other energy services. In order to allow some comparison to be made between different premises, some scaling factor is required to correct for this effect. A common approach is to scale by the floor area of the premise. Scaling the energy use in this way produces a figure known as the Energy Use Intensity (EUI) for that premise. The energy use for the whole building (base building and premises) and the total floor area for the building could also be combined to calculate an Energy Use Intensity for the whole building (Peterson and Crowther, 2010).
3. Considering today’s buildings Until BEES the data on the energy performance of New Zealand’s non-residential buildings was very limited. In the late 70’s and early 80’s there were a number of projects in the three main centres; Auckland (Beca Carter Hollings et al., 1979), Wellington (Baird, et al. 1983) and Christchurch (R. W. Morris & Associates, 1985), which examined the energy performance of commercial buildings in those specific areas. Making use of the results from
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these studies today introduces some difficulties due to the changing building standards, insulation levels and HVAC performance. These earlier studies also were localised, selecting commercial buildings in a restricted area. This has the potential to bias the sample towards larger commercial buildings. Around the same time Standards New Zealand (1982) developed guidelines for energy efficiency in non-residential buildings which included suggesting for buildings with particular activity types such as a target of an EUI of less than 100 kWh/m²•year for new office buildings. While these targets are still frequently used today, their origins are not commonly stated, perhaps not wishing to reveal the uncertainty in these targets. In designing new non-residential buildings, a common means to assess how it will perform with regard to energy use is to use building energy simulation computer programs. Current building code requirements allow for building energy simulation programs to be used providing they meet certain requirements (Standards New Zealand, 1996; Judkoff and Neymark, 1995). While building energy simulation programs can provide accurate estimates of a buildings energy use, this is dependent on having an extensive data set of building characteristics, weather information and accurate schedules of HVAC, occupancy and other equipment operation. These data sources are often not available and estimates are made reducing the accuracy of the building energy modelling. Indeed often schedules and inputs from overseas are used. Lunneberg (1999) commented that equipment load calculations for use in building simulations are frequently over estimated and that this estimate can be out by as much as five times the measured load. Detailed measuring of equipment load demands is expensive and can only be done once the building has been constructed and occupied. This has been done within the BEES project and the BEES energy monitoring provides an opportunity to explore how appliances are actually used in non-residential buildings. This provides a better understanding of the actual appliance loads within New Zealand’s non-residential buildings and will allow better estimates to be made of aggregate appliance use for use in computer simulations of nonresidential buildings.
4. Using BEES data to examine appliance loads in more detail As part of the energy monitoring in BEES, at least three randomly selected appliances within each of the premises were measured over the two week monitoring period. These measurements were undertaken at a one-minute time interval to allow the characteristics of fast switching services to be examined in detail. For example, a refrigerator that cycles at say, a 14 minute period would always appear on if examined at the frequently used halfhourly interval.
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This paper will consider computers as an example of a particular appliance load (part of the equipment load) for a non-residential building showing the pattern of typical use as well as how varied that use is. Figure 1 is a standard exploratory data analysis (EDA) graph used within the BEES project. This type of data presentation and initial analyses supported by very high density monitoring provides an enormous amount of useful information where significant insight can be drawn from this type of data. Figure 1 shows a typical pattern of a desktop computer over twenty one days in a standard office environment. The measurement intervals are 1-minute which allows subtle patterns to be examined such as certain categories of loads (wattage), abnormalities (negative readings – either due to the inductive loads or instrument error – fluctuations, we can analyse how frequent and how significant these are), daily profiles, start and end of working hours, time and intensity of operation during each day, spikes and base loads. For example someone was working for a short period of time on Saturday 29 May and the computer was not used at all on 3 June, as it turns out this was a holiday weekend (Queen’s Birthday) in New Zealand. A detailed description of these EDA graphs can be found in the BEES literature (Isaacs, et al 2010). R0079AA5 CompEof8a 22/11/2012 20:29:18
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Figure 2 gives the electricity use of one computer over one day at a one minute interval. This fine timescale allows for a detailed appreciation of “fine cycling” including clear distinctions when the processor and hard drive were performing harder. It was used in a standard office and it expected that only light processing such as word processing or basic spreadsheets were used rather than intensive processor tasks. There is a distinct but not particularly significant peak during the lunch time. Could this be lunchtime social activities which are more intensive in computer usage such as; playing games, checking social media or using the CD drive to listen to music?
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The twenty-one individual days of use of the computer are presented in Figure 3 scaled to 10 minute intervals to better recognise repeated behaviours. Figure 3 also shows in heavy black outline, the average time of day profile for the computer. This average profile is lower than the typical operating level due to the computer not always being on at that time of day. The level of the average profile will be reduced with the computer not being used on weekends and holidays as well as periods of the computer user being out of the office. The one day the computer being used in the evening results in a small blip (1/21 of the typical operating level) in the average profile for the evenings.
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At least one feature is clearly identifiable; the computer is being used in a very consistent way and for particular regular tasks. When compared to other computers in the building, we observed similar profiles. Thus at least in this case it is quite simple to estimate the profile and the way the energy is used by computers in this business.
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For the purpose of this analysis we have selected fifteen computers in different premises available from the BEES database. Two thirds of these computers were in offices with the remaining third in retail premises. Figure 4 gives the value of the estimated annual energy use (in kWh) of the fifteen computers examined in descending order. Computers present in offices are identified by the dark grey bars whereas computers in retail business are identified by the light grey bars. These computers were for individual use and did not include a display other than when this was an integrated feature of the computer (such as a laptop). The energy is collected when
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the computer is used at the monitored premise. Laptops which are used away from the premise will only have the data from when the computer is present at the business recorded. The monitoring for the laptops is not of the operation of the laptop (as laptops can operate from batteries) but instead is when the computer is connected to an electrical outlet and using electricity. The top three (20%) computers in the energy rankings were computers that were left on outside of the business hours. This 20% is similar to the proportion of computers in the United States of America that were identified as being ‘on’ outside of normal hours (Webber, 2005). These three computers use considerably more energy per computer than is the case for any of the other computers. The three laptop computers (ID’s 10,12 and 15) were lower energy using computers. The highest energy using computer used more than forty times the energy than of the lowest energy using computer. 450 Annual computer energy use (kWh)
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Figure 5 gives the electricity time of day demand of fifteen different computers. Apart from the three computers that are left on outside of working hours, and the lowest energy using computer shown in the bottom right hand corner of Figure 4. All of the computers show an approximate square wave shape increasing energy use from around 8-9 o’clock in the morning and running until around 17-18 o’clock before dropping back to a standby load level outside of working hours. The differing factors for each of these computers are the power requirements during the operating houses as well as the varying standby power requirements outside of normal hours. The standby load varied from around 2 W to 10 W. One system appeared to have no power requirements outside of operating hours. It is likely this system was turned off at the end of the day rather than being set to standby.
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5. What this means for buildings for tomorrow Building energy simulation is currently the primary means to examine the energy impacts of various building design options. While building energy simulation programs accurately determine the physical heat transfer processes going on within a building, they are dependent on having accurate information on the operational characteristics of the building such as the occupancy, HVAC and other equipment use. The BEES data is revealing some of the variability present within equipment operation which will allow more realistic equipment schedules to be developed in the future. The operational characteristics are ultimately dependent on the people using the building. While using more accurate equipment schedules will allow a more accurate calculation of the building energy to be made, there still may not be sufficient variation in the scheduling to
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accurately summarise the collective behaviours of the building uses. A framework to better understand building energy will require drawing together physical building energy simulation models with behavioural models of what the users of the building are doing. One emerging method to examine behaviours of a set of individuals is agent-based modelling (Macy and Willer, 2002). Agent-based modelling uses large scale computer based calculations of a set of basic rules on a number of agents within a target population. Agentbased modelling has had some application to energy use in buildings. Azar and Menassa (2012) is one such example, however this paper looked to examine the impacts of behavioural change, turning high energy consuming users into low energy uses, rather than in better understanding the overall operation of a building. Perhaps there is an opportunity for agent based modeling to be used to provide a range of operational schedules for input into building energy simulation models in an analogous way to have varying weather data is examined by considering a full year of data. Building energy simulation provides a means to assess the energy impacts of a variety of design choices. Building energy simulation can be used to set targets for the energy use for a particular building by setting a level of maximum energy use that can only be achieved by incorporating good thermal design and a well performing HVAC system into the building. Care must be taken to ensure that a building’s actual operating energy use is aligned with its design levels. Turner and Frankel (2008) highlight that this is not always the case with many ‘high scoring’ buildings actually requiring more energy that is set as a maximum for the code requirements (see figure ES-5 in Turner and Frankel, 2008).The overall energy use in the BEES buildings will provide some indication of variability of real building energy performance. This performance information will help to inform the setting of any performance thresholds for new buildings but would also assist the setting of targets for the retrofitting and upgrading of existing non-residential buildings. The Energy Efficiency and Conservation Authority (EECA) and the New Zealand Green Building Council (NZGBC) have announced (EECA, 2012) that they will be developing a New Zealand version of the Australian NABERS (National Australian Built Environment Rating System) scheme which looks to assess buildings on their measured energy performance. BEES has provided energy use intensity information to the developers to assist with benchmarking against standard New Zealand buildings.
6. Acknowledgements BEES is funded by BRANZ Ltd. through the Building Research Levy and the Ministry of Business, Innovation and Employment through its Building and Housing group and its Science and Innovation group. The Energy Efficiency and Conservation Authority (EECA) has also contributed to the funding for this project.
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References Azar, E and Menassa, C (2012) ‘Agent-Based Modeling of Occupants and Their Impact on Energy Use in Commercial Buildings’, J. Comput. Civ. Eng., 26(4), 506–518. Baird, G, Donn, M and Pool, F (1983) ‘Energy demand in the Wellington central business district’. New Zealand Energy Research and Development Committee. Report 77, February 1983. ISSN 0110-1692. Beca Carter Hollings and Ferner and R Shaw. (1979). ‘Greater Auckland commercial sector energy analysis. New Zealand’ Energy Research and Development Committee. Report 45, May 1979. ISSN 0110-1692. Camilleri, M and Isaacs, N (2010) “The Building Energy End-use Study (BEES): Study Design and Early Findings” Proc. CIB 2010 World Congress, 10-13 May 2010, Salford Quays UK. EECA (2012) ‘Office building rating scheme coming to http://www.eecabusiness.govt.nz/content/office-building-rating-scheme 21 November 2012.
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Isaacs, N (ed.), Saville-Smith, K, Babylon, W M, Bishop, R, Camilleri, M, Donn, M, Jowett, J, Moore, D, and Roberti, J (2010) ‘Building Energy End-Use Study (BEES) Year 3’, BRANZ Study Report SR 236, BRANZ, Porirua. Isaacs, N (ed.), Saville-Smith, K, Bishop, R, Camilleri, M, Jowett, J, Hills, A, Moore, D, Babylon, W M, Donn, M, Heinrich, M, and Roberti, J (2009) ‘Building Energy End-Use Study (BEES) Years 1 & 2’, BRANZ Study Report SR 224, BRANZ, Porirua. Judkoff, R and Neymark, J (1995) ‘International Energy Agency Building Energy Simulation Test (BESTEST) and Diagnostic Method’; NREL/TP-472 6231, National Renewable Energy Laboratory Colorado, USA Lunneberg, T (1999) ‘Improving Simulation Accuracy Through the use of Short-Term Electrical End-Use Monitoring’ Proceedings of the International Building Performance Simulation Association Conference 1999. Macy, M W and Willer, R (2002) ‘From Factors to Actors: Computational Sociology and Agent-Based Modeling’, Annual Review of Sociology Vol. 28, pp. 143-166 Peterson, K and Crowther, H (2010) ‘Building EUIs’, High Performing Buildings, Summer 2010, ASHRAE. R. W. Morris & Associates. (1985) ‘Commercial sector energy use in Christchurch’. New Zealand Energy Research and Development Committee. Report 115, September 1985. ISSN 0110-1692.
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Saville-Smith, K and Fraser, R (2012) ‘Building Energy End-Use Study (BEES) Interim Report: Buildings – Size, Management and Use’. BRANZ Study Report SR 277/1, BRANZ, Porirua. Standards New Zealand (1982) ‘NZS4220:1982 Code of practice for Energy Conservation in Non-Residential Buildings’. Standards New Zealand, Wellington. Standards New Zealand (1996) ‘NZS4243:1996 Energy Efficiency – Large Buildings’. Standards New Zealand, Wellington. Turner, C and Frankel, M (2008) ‘Energy Performance of LEED® for New Construction Buildings’, Report for: U.S. Green Building Council by the New Buildings Institute, Vancouver, Washington, USA. Webber, C A, Roberson, J A, Brown, R E, Payne, C T, Nordman, B Koomey, J G (2005) ‘Field Surveys of Office Equipment Operating Patterns’ Report LBNL-46930, Lawrence Berkeley National Laboratory, Berkeley.
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Challenges and Opportunities of Low or Zero Carbon Building: Prospects of Business Models Wei Pan1, Larch Maxey2 Abstract There is an emerging consensus amongst governments, business sectors and civil societies regarding the urgent need to address the multiple challenges of climate change, environmental pollution, resource depletion and economic instability. The building and construction sector has been identified with the most opportunities for cost-effectively reducing carbon emissions. However, although business opportunities have been identified for low or zero carbon building (L/ZCB), L/ZCBs are generally perceived as more expensive and challenging than conventional buildings. Also, L/ZCBs are often addressed solely from their technological and environmental perspectives, while important economic and sociocultural aspects have been overlooked or examined implicitly. This paper aims to contribute to the knowledge of the challenges and opportunities of L/ZCB in a systems manner, and to explore how business models can help construction organisations address the former and maximise the latter. The research was carried out through the combination of a comprehensive literature review and case study with a large construction organisation which played a significant role in the UK and internationally. The examination of the challenges and opportunities employed the PESTEL analysis framework (Political, Economic, Sociocultural, Technological, Environmental and Legal). The case study included a desk study, observations, meetings and personal interviews with senior business and sustainability managers of the company. The results suggest the imperative role of business models for L/ZCB developments. Establishing and innovating business models were considered to present an opportunity for the company to sharpen their competitive edge in the market. A wide take-up of business models of L/ZCBs among construction firms was perceived to fit well the building industry's socio-technical system in addressing the multiple challenges. Keywords: Low or Zero Carbon Building, Business Models, Socio-technical, PESTEL Analysis, Systems Approach.
1. Introduction Rapidly growing energy use worldwide has raised concerns over the problems of energy supply and security, which contribute to the multiple challenges of climate change, environmental pollution, resource depletion and economic instability. Practically all major greenhouse gas emitters now have climate change legislation (Townsend et al., 2011), which will form the basis of a global agreement to be reached by 2015 (Fankenhauser,
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Department of Civil Engineering, The University of Hong Kong, Hong Kong,
[email protected]. Plymouth University, Plymouth, UK,
[email protected].
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2012). Buildings, as a whole, contribute the biggest single proportion to total energy consumption in many countries, accounting for up to half of primary energy resources (Butler, 2008; Pérez-Lombard et al., 2008). The building and construction sector has been identified with the most opportunities for cost-effectively reducing carbon emissions and helping to address the multiple challenges (IPCC, 2007). In the UK, the built environment accounts for an estimated 40% of total energy consumption and produces 50% of all UK carbon emissions (CLG, 2007a). The UK government has committed to reduce carbon emissions by at least 80% over the 1990 baseline by 2050 and set ‘zero carbon’ targets for all new dwellings from 2016 (CLG, 2007a) and non-residential buildings from 2019 (CLG, 2008a). The UK government has described achieving these targets as a ‘transformation in its [the construction industry’s] own structure and practice’ (HM Government, 2010: 2), which requires ‘a revolution in the way we build, design and power our homes’ (CLG, 2007b: 9). The UK government's Business Link (2011) elaborated a range of business opportunities introduced by the transition to the low carbon economy in a variety of business sectors, of which a significant one is low or zero carbon building (L/ZCB). It has been suggested that ‘Over the next 40 years, the transition to low carbon can almost be read as a business plan for construction, bringing opportunities for growth’ (HM Government 2010: 4). However, L/ZCBs are being addressed in many cases solely from their technological and environmental perspectives, while other important aspects, e.g. economic and socio-cultural, have been overlooked or examined implicitly. This approach is problematic, as the construction industry faces multiple challenges in delivering buildings of quality, quantity, affordability and environmental sustainability (Goodier and Pan, 2010). The concept of business models only became widely prevalent with the advent of the Internet in the mid1990s. Teece (2010) pinpointed that the concept of a business model lacks theoretical grounding in economics or in business studies, and quite simply there is no established place in economic theory for business models. These features inevitably introduce a source of confusion and obstruction to research in business models. While L/ZCBs are generally perceived to be more expensive and challenging, the opportunities and benefits of establishing and innovating their associated business models remain largely unknown. Therefore, this paper aims to contribute to the knowledge of the challenges and opportunities of L/ZCB in a systems manner, and to explore how business models can help construction organisations address the challenges and maximise the opportunities. The exploration is conducted within the UK context, while the discussion draws on the wider knowledge base where possible.
2. Research method This research was carried out through a combination of a comprehensive survey of the literature and case study with a large construction organisation which played a significant role in L/ZCB developments in the UK and internationally. The examination of the challenges and opportunities of L/ZCB drew on a systems approach. Research highlights the importance of resisting the temptation to focus on the physical aspects of construction but adopting a holistic approach to sustainable construction development (Pearce, 2003; Butler, 2008). Such a holistic approach is crucial to L/ZCB,
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where there may be a tendency to focus rather narrowly on buildings’ technical details, yet the far reaching nature of L/ZCBs’ ‘transformation’ (HM Government, 2010: 2) requires a systems approach to address the broader context of L/ZCBs. The systems approach has been noted by several studies within the context of new buildings (Glass et al., 2008; Osmani and O’Reilly, 2009; Goodier and Pan, 2010), and more generally in climate change policy (Fankenhauser, 2012). This present paper therefore uses a PESTEL analysis to examine the political, economic, socio-cultural, environmental, technological and legal factors associated with L/ZCB, so that ‘a systems approach could shed new light on the problem’ (Glass et al., 2008: 4535). This PESTEL framework also guided the exploration of ways, in which business models can support L/ZCB developments. The case study company was an international property and infrastructure group operating in forty countries, with a typical turnover of £900 million for its UK operation. The integrated approach to business of this company spanned activities from identifying and developing land, through construction to property management. The company’s long-standing commitment to sustainability has evolved into an aspiration to be a global leader in sustainability. The case study comprised: (1) a desk study of the organisation’s websites, brochures, reports and publications on the business’ mission, objectives and strategies regarding L/ZCB; (2) meetings with key members of its senior sustainability and business managers, including the Head of Sustainability (HoS) for Europe, the Middle East and Africa (EMEA) who reported directly to the CEO, and the Senior Manager of Sustainability (SMoS); (3) observation of the presentations made by the CEO, and the HoS and the SMoS at two distinguished national conferences, which covered the topic of L/ZCB and the company’s practice and business strategies; and (4) personal interviews with the HoS and the Head of Strategy and Business (HoSB) on an individual basis. All these participants had a strategic company-wide remit. For the interviews a list of questions was provided to the interviewees beforehand, which helped to improve the efficiency of data collection and quality of data collected. Each interview took around an hour. All the interviews were audio recorded. Transcripts verified by the interviewees, together with the notes obtained of the meetings and the presentations were used for qualitative analysis. The analysis followed the logic of identifying and verifying codes, themes and patterns.
3. Challenges and opportunities of L/ZCB: PESTEL analysis The challenges and opportunities of L/ZCB are examined below in each PESTEL aspect. However, these challenges and opportunities are interrelated and should therefore be interpreted together. Therefore, cross-aspect discussion is made where possible.
3.1 Political aspects Politics presents pivotal opportunities for L/ZCB. The opportunities exist at a number of levels: 1) internationally, e.g. as introduced by EU energy efficiency legislation, the international climate change framework being developed by 2015 (Fankenhauser, 2012), improving cross governmental communication and cooperation, integrating of demand and supply side policies (Glass et al., 2008) and government-led ‘golden carrot competitions’ to stimulate supply chain reform (Lowe and Oreszczyn, 2008: 4480) as up to 86% of a
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company’s total emissions are via their supply chain (indirect emissions) (Matthews et al., 2008); 2) nationally, in the case of UK, for all new domestic buildings to be zero carbon from 2016 and all non-domestic buildings from 2019 (CLG, 2008b); and 3) regionally, e.g. by the London Borough of Merton’s game-changing promotion of on-site new build renewable energy generation (Lowe and Oreszczyn, 2010; Osmani and O’Reilly, 2009; CLG 2011). However, there exist severe challenges to L/ZCB as well. A critical one is the uncertainty of the definition of L/ZCB (i.e. what exactly a L/ZCB constitutes), which remains within the above-mentioned multi-level policy landscape (HM Government, 2010; Lowe and Oreszczyn, 2010; Osmani and O’Reilly, 2009). This definition-related uncertainty, albeit containing technical, economic and socio-cultural dimensions, is fundamentally a political challenge as governments define L/ZCB inconsistently. This inconsistency is illustrated by the inclusion of off-site renewable energy generation for L/ZCB, in the case of the UK, from 2012 (CLG, 2011). The uncertainly of the L/ZCB definition is also directly or indirectly attributed to many other policies, e.g. the UK’s loss of stamp duty exemption, unstable feedin-tariff regime, the way new policies such as the Green Deal and National Planning Policy Framework emerge (see Osmani and O’Reilly 2009), a lack of joined up thinking between difference policy areas such energy and housing and poor communication between government departments (Lowe and Oreszczyn, 2008). This challenge is also global, illustrated by the lack of clear consistent policies addressing climate change internationally (Fankenhauser, 2012). Nevertheless, despite the uncertainty of the definition being a critical challenge, the ability to change the definitions of L/ZCBs presents opportunities for L/ZCBs to be responsive to the changing PESTEL factors, e.g. market demand, emerging technologies, scientific evidence and social trends, which introduces business opportunities to those who pro-actively engage with L/ZCBs.
3.2 Economic aspects The ‘recent sharp economic downturn’ is a key economic challenge to L/ZCB (Goodier and Pan, 2010: 4). In addition to the economic instability, climate change and peaking fund resources are likely to result in significant economic contraction, particularly in the Minority World (Glass et al., 2008). The scale of the challenges and responses required renders current incremental approaches to building provision reform based on ecological modernisation insufficient (Lowe and Oreszczyn, 2008; Jackson, 2009). There is a growing New Economics literature on degrowth (Sekulova et al., 2013), circular (Jackson, 2009), steady state (Daly and Cobb, 1990) and free (Boyle, 2012) economy models and strong sustainable consumption (Røpke, 2009). These perspectives highlight further limitations in current L/ZCB initiatives, including their focus on the metrics of carbon rather than more holistic approaches to sustainability which embrace social justice and socio-culturally inscribed patterns of consumption of, through and within buildings. An underlying commitment to economic growth may predispose policy makers and developers to missed important opportunities or glaring paradoxes. New Economics’ implications for L/ZCB building provision remains a significant research gap. Seyfang (2010) suggested small scale, grassroots models of L/ZCB construction have the potential to both upscale and inform mainstream L/ZCB provision. While some commentators identified that small operators remain at the forefront of L/ZCB development (Lowe and Oreszczyn, 2008; Seyfang, 2010;
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Peterman et al., 2012), these approaches remain on the margins of current policy and practice. Isiadinso et al. (2011: 444) considered ‘achieving economies of scale as a crucial aspect of the uptake of low carbon buildings.’ Furthermore, efficiencies of scale may enable L/ZCB compliance (Pan and Garmston, 2012) and interest in and experience of L/ZCB amongst volume builders is burgeoning (Osmani and O’Reilly, 2009; Bell et al., 2012). Second to the challenge presented by the economic growth paradigm is the perception of L/ZCBs as more expensive. Although as Lowe and Oreszczyn (2008: 4479) noted, ‘the most cost effective measures in existing and new UK housing have already been undertaken’ and L/ZCB is often currently more expensive (CLG, 2011), industry perceptions of L/ZCB’s costs exceed reality (NNFCC, 2010; Dunster, 2012). The industry uncertainties regarding both costs and demand for L/ZCB are significant challenges (Lowe and Oreszczyn, 2008), particularly due to the conservative nature of the industry. However, despite the many challenges, economic opportunities abound. Research suggests there is already significant demand for L/ZCBs (Osmani and O’Reilly, 2009; Bell et al., 2010) and there are considerable opportunities for this to grow and support L/ZCB as energy prices escalate, fund resource supplies become less stable and external costs are internalised more effectively (Jackson, 2009; Sekulova et al., 2013). There are many opportunities to help internalise external costs within energy and construction which would make L/ZCB the most economically attractive option, these include Tradeable Energy Quotas tax and other pricing mechanisms (Jackson, 2009). While cost challenges render L/ZCB sales premiums neutral, L/ZCB becomes a net boon through the marketing, market differentiation, reputation and early intervention cost saving it represents (Osmani and O’Reilly, 2009). Pro-active L/ZCB engagement can lead to enhanced brand recognition and reputation as well as being more cost effective in meeting L/ZCB standards as they become more stringent (Carter, 2006). L/ZCB also protects against the business risks of future legislation, widespread adoption of carbon accounting methods and increasing costs of current construction methods (Glass et al., 2008). Government can enhance these opportunities through fiscal based legislation (Glass et al, 2008) such as the UK’s Green Deal, providing grants and facilitating the trend towards socially responsible investment funds accessible to L/ZCB.
3.3 Socio-cultural aspects The key socio-cultural challenges to L/ZCB include the construction industry’s conservative nature and the limited public awareness of and demand for L/ZCBs. Industry challenges include widespread risk-averse attitudes and reluctance to innovation (Lowe and Oreszczyn, 2008), skills shortages (Glass et al., 2008), slow take-up of sustainability (Pearce, 2003) and a fragmented structure with few large and many small players (Glass et al., 2008; Pan and Goodier, 2012). Many in the industry are unwilling to adopt what they view as untested technologies (Osmani and O’Reilly, 2009). Given the new knowledge, new skills, innovation and holistic/integrated approaches required for LZCB (Peterman et al., 2012) and L/ZCB’s necessary ‘revolution’ (CLG, 2007b: 9), the lack of ‘collaborative integration of the supply chain and silo-based habits of the industry’s institutions’ (HM Government, 2010: 7) presents a significant challenge to developing, communicating, implementing and monitoring new L/ZCB products and approaches. Glass et al. (2008: 4534-5) note the industry’s traditional, conservative disposition ‘under-performing legacy’ and ‘begrudging response’ which mean
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that ‘In the short term at least, change needs to be imposed top-down, and supported bottom-up with encouragement and reward.’ The industry’s perception of fluctuating (Peterman et al., 2012) or low demand for L/ZCBs amongst clients (Osmani and O’Reilly, 2009) and the general public (Lowe and Oreszczyn, 2008) is another challenge, compounded by concerns such as ’sick building syndrome’ due to high levels of air tightness (Lowe and Oreszczyn, 2008) and the aesthetics and space of on-site renewable (Isiadinso et al., 2011). This is exacerbated by the industry’s poor reputation and criticisms of greenwash and ‘spin’ (Glass et al., 2008). Nevertheless, there exist important socio-cultural opportunities for L/ZCB. Osmani and O’Reilly (2009) rank them second only to mandatory legislation in their potential to drive L/ZCB. The industry’s highly concentrated nature (Pan and Goodier, 2012) affords opportunities, as well as challenges, for L/ZCB, as once volume builders commit they can rapidly roll out L/ZCB and put greater resources to the challenge, whereas educating, training and committing numerous SMEs may be slower and more difficult. The tension here is that L/ZCB innovation has been driven by small firms and particularly grass roots initiatives (Seyfang, 2010; Peterman et al., 2012). L/ZCBs offer reputational benefits spanning from the wide industry to specific projects, which lead to further opportunities. L/ZCBs can help build, rather than ‘consume’ human capital (Lowe and Oreszczyn, 2008), encourage staff to be more IT-literate and informed on specification/design (Harty et al., 2007), attract high calibre employees and draw upon a ‘growing carbon culture’ which government as well as industry can build upon (Osmani and O’Reilly, 2009: 1918). The L/ZCB agenda could help transform the industry’s culture, inculcating more team working (Glass et al., 2008) and partnerships with local councils (Osmani and O’Reilly, 2009).
3.4 Technological aspects The technological aspects also see challenges as well as opportunities of L/ZCB. Previous research pinpoints that due to concerns regarding on-site renewable energy particularly and the constraints imposed by volume builders’ standard house sets, ‘Technical and design barriers are one of the main considerations’ for L/ZCB (Osmani and O’Reilly, 2009: 1928). These barriers are related to the socio-cultural challenges identified, with evidence that the main issue is not the limitations or cost of L/ZCB technology, but industry’s ability to embrace it. Dunster (2012) indicated that solar photovoltaic panels’ halving in price within six months during 2012 makes their cost comparable with conventional cladding materials, but the industry has been unable to change its design, sourcing and specification processes at the same rate, whilst 100% renewable/recycled materials can save 10% on the cost of conventional materials to the same L/ZCB standard (NNFCC, 2011). Even greater cost, energy, time and materials savings can be made from off-site L/ZCB construction (Goodier and Pan, 2010) and on-site use of robotics (Glass et al., 2008). Technology such as smart meters supports L/ZCB directly and enables such real-time data collection, whilst the growing field of citizen science and collaborative research enhance opportunities for responsive data collection, analysis and engagement. Organisations such as the Transition Research Network and their ability to tap into viral grassroots socio-cultural technologies such as Transition Streets offer significant potential to go much further than Lowe and Oreszczyn’s call to ‘share knowledge from the fringes’ (2008: 4479).
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3.5 Environmental aspects In the environmental aspects, the main challenge relates to extreme weather effects potentially undermining L/ZCBs. For example, climate change triggers flooding more likely, which requires additional tanking that involves the use of materials such as concrete with high levels of embodied energy and other resources. Also, environmental challenges intersect with socio-cultural factors, e.g. the rebound effect (Jackson, 2009; Pan and Garmston, 2012; Isiadinso et al., 2011), whereby extreme weather such as heat waves leads to the inappropriate bolting-on of air condition to what are otherwise L/ZCBs. The ‘resilience agenda’ (Glass et al., 2008; ) therefore highlights the need for L/ZCB to address adaptation to, as well as mitigation of, climate change and peaking resources (Harty et al., 2007) in order to avoid exacerbating problems associated with extreme weather events, but also dwindling fund resource supplies and terrorism (Glass et al., 2008). To address environmental concerns has introduced opportunities for L/ZCB. Whilst extreme weather events challenge L/ZCB in some respects, the more extreme they are, the more L/ZCB will benefit, as they further raise the growing awareness of climate change and the triple challenge which L/ZCB is uniquely placed to address. Embracing resilience affords L/ZCB opportunities through forward planning, so that problems become solutions.
3.6 Legal aspects Previous research shows that the views and practices of housebuilders (Osmani and O’Reilly, 2009) and virtually all aspects of the construction industry (Lowe and Oresczyn, 2008; Pan and Garmston, 2012) respond to mandatory legislation, rather than policies, voluntary schemes or softer mechanisms (Peterman et al., 2012). This presents a legal challenge to L/ZCB. Also, the relationship between voluntary and mandatory L/ZCB standards is not simple or fixed. Many L/ZCB standards begin as voluntary and become mandatory, as demonstrated by the UK L/ZCB framework (CLG, 2008a,b, 2011). In addition, the greatest legal challenge to L/ZCB concerns enforcement, with Glass et al. (2008) critiquing that L/ZCB legislation lacks teeth and Lowe and Oresczyn (2008: 4477) suggesting that it needs to be 'vigorously and rigorously enforced’ to overcome the lack of resources for regulatory development and implementation. Pan and Garmston (2012) found that a lack of awareness and training among both industry and building control officers created uncertainty and contributed to significant discrepancies between mandatory standards and actual building performance. Furthermore, the legal challenges relate to the ‘less-than-responsive planning system’ (Goodier and Pan 2010: 4). Nevertheless, mandatory standards are the most potent way to support L/ZCB. The legislation can play a facilitative role for L/ZCB, and often gives rise to new business opportunities and new/adapted business models. Also, the legal-side opportunities may be maximised when the transition from voluntary to mandatory standards occurs within a clear consistent timeframe which achieves wide-ranging buy-in.
4. Business models of L/ZCB Business models are not new phenomena, and their study is an emerging, contested, interdisciplinary field (Teece, 2010). A typical interpretation of business models is that it ‘defines how the enterprise creates and delivers value to customers, and then converts
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payments received to profits’ (Teece, 2010: 173). Mason and Spring (2011: 1033) noted that until 2000 the notion was restricted to internet businesses at the network level, yet its wider adoption has seen it applied almost exclusively to the firm, leading them to argue for dynamic, networked and performative understandings of business models capable of ‘zooming in and out’ to investigate their operation at the firm, network and industry levels. Building research has been slow to grasp the importance of business models and lags behind the fields such as business and management where the concept has been developed. Also, building research often mistakenly equates business models with competitive advantage theory (Pan and Goodier, 2012) and presents business models as factual statements, rather than being emergent, dynamic and performative as argued by business model researchers (e.g. Mason and Spring, 2011; Teece, 2010).
4.1 Prospects of business models for L/ZCB Greater attention to business models should help address the challenges and maximise the opportunities of L/ZCB, which are identified through the PESTEL analysis in this paper. There prospects of business models for L/ZCB are multi-fold. First, part of their value concerns business models’ agency to shape actions as well as being shaped by the actions of others within firms, networks and across the industry (Mason and Spring, 2011). For example, business models shape demand as well as respond to it (Teece, 2010; Mason and Spring, 2011). This directly relates to the opportunities and challenges regarding industry’s assertion of L/ZCB demand (Lowe and Oreszczyn, 2008; Osmani and O’Reilly, 2009). Second, business models’ emphasis on a ‘deep understanding of the user’ (Teece, 2010:190) and initial findings which contradict these assertions (Bell et al., 2010) highlights the importance of market research and similar work for L/ZCB and as L/ZCB business models emerge they will stimulate market research and other work deepening industry understandings of users. Third, business models may allow government policy and corporate sustainability strategies more agency in shaping L/ZCB, including opportunities to impact on buildings’ in-use impacts and occupants’ behaviour patterns.
4.2 Business model take-ups in the building industry There is a need to address business models across the industry as a whole (HM Government, 2010). Teece’s (2010: 189) observed that ‘long-lived structural elements – choices made perhaps decades ago in different environments – need to be scrutinized especially thoroughly.’ Such scrutiny could help create the socio-technical changes needed for L/ZCB. For example, volume builders’ use of standard house types could be addressed through developing business models which integrate more responsive designs capable of the pace of changes in the PESTEL aspects. However, there also exist tensions with using business models to support L/ZCB. For example, it is asserted that business models must be ‘non-imitable’ (Teece, 2010: 192), while the urgency and scale of the multiple challenges require that L/ZCB business models are rolled out as comprehensively as possible.
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5. Case study results The case study company aspired to become a leader in sustainable development. This aspiration has been driven by a long-standing commitment to sustainability initiated by the founder of the company who as early as in 1973 suggested that the society would soon place emphasise on environmental and social impacts above economics. Although there was limited explicit mission of policy relating to L/ZCB, L/ZCB was embedded in its sustainability objectives including the aspiration that all the buildings it developed and/or operated are zero net carbon, water and waste as a minimum. The desk study revealed no evidence of explicit commitment to business models of L/ZCB. However, there were elements which indicated the potential for this, including aspirations to engage only with organisations aligned with the case study’s aspirations, ethics and values, to operate and ensure its suppliers operate in accordance with the UN Global Compact 10 Principles and to be a recognised leader in facilitating learning and professional development with its suppliers. Furthermore, the company’s 2011 Sustainability Report identified six Core Values of respect, integrity, excellence, trust, innovation and collaboration. These all pointed to the importance of supply chains, public accountability, innovation and collaboration, areas where business models can support L/ZCB innovation. Through the interviews it became clear that the company was explicitly and actively involved in L/ZCB developments and innovation, going beyond regulatory requirements and shaping policy through positions on the UK Green Business Council and Green Construction Board. For example, the HoS commented, ‘there is no definition yet on what certain code levels are for high rises…so we want to be among the first to do that and we also want to be involved in determining what that looks like and how feasible that is.’ The interviewees confirmed the PESTEL analysis in identifying uncertainty as a key challenge, including political and economic and definition-related uncertainty. However, this also encouraged their proactivity in shaping emerging definitions of L/ZCB and turning this challenge into an opportunity. The HoS identified the importance of legislative drivers to push ‘quite conservative, traditional industries’ forward, while as individuals and a company they were motivated by L/ZCBs’ pivotal role in reducing global carbon emissions. The HoSB added, ‘the main drivers are really around reputation, staying ahead of the competition, and also ahead of legislation’. L/ZCB provided opportunities to gain ‘a competitive edge as a company in winning tenders and also in convincing clients, consumers to purchase and move into places like this’ (HoS). L/ZCBs are ‘more attractive for end-users…there are lots of benefits, not only in terms of energy reduction, but also… the social and economic benefits of this agenda, and how it can really add value to our business’ and ‘around health, productivity and wellbeing of the people within those buildings’ (HoSB). Economic challenges were also identified, ‘one of the main challenges for the wider industry is getting the whole life costs of the building to work with the right players getting the financial benefits of low and zero carbon buildings’ (HoSB). The respondents felt that such challenges could be addressed through education as well as government and industry embracing whole life costings. It is clear that these measures could be supported by business models. The HoSB emphasized that, ‘the measures introduced are varied but should appeal to large businesses and also embrace SMEs.’
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The company’s size and scale meant they operated a range of different business models, with larger projects offering more scope for L/ZCB business models, including working closely with suppliers to develop new energy efficient products and to build and manage. The HoS explained, ‘working together with our supply chains, we develop, build and manage, so we can also influence our supply chains’ longer term sustainability aspirations.’ The company also proactively engaged with their clients and customers. The HoSB elaborated, ‘we look at how we can make sure that we are educating future customers and consumers or the users of those homes; that they have also got the right information; and that they get the best out of those buildings.’
6. Conclusions L/ZCB introduces significant challenges to, but also presents unprecedented opportunities for, the building industry to address the multiple challenges of climate change, environmental pollution, resource depletion and economic instability. By employing a systems approach this paper has examined the political, economic, socio-cultural, technological, environmental and legal aspects of the challenges and opportunities. The results indicate that these challenges and opportunities are interactive and dynamic: exist in no isolation but evolve and interact in parallel. Some challenges might be perceived as opportunities and vice versa, depending on the positions and aspirations of different stakeholders. The political and legislation drivers have vital roles to play in fostering changes within the building industry. The environmental and technological aspects are more embedded in mentality of the industry. However, the role of economic and socio-cultural drivers can be enhanced. All these together generate significant prospects of business models of L/ZCB which can support innovative L/ZCB developments, helping forge pathways to sustainable, closed-loop economic and sociotechnical systems. However, business models have received little attention within both the literature and practice of L/ZCB. The approaches already being adopted by industry leaders such as those featured in the case study demonstrate the importance of further attention to business models’ role in L/ZCB within policy, research and practice. A wide take-up of business models of L/ZCB should help to accelerate L/ZCB practice and enable the building industry to play its full role in addressing the multiple challenges.
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Post-Occupancy Evaluation Studies in a recently Refurbished Office Building: Energy Performance and Employees’ Satisfaction Michelle Agha-Hossein1, Sam El-Jouzi2, Abbas Elmualim3, Judi Ellis4, Marylin Williams5 Abstract Existing buildings contribute greatly to global energy use and greenhouse gas emissions. In the UK, about 18% of carbon emissions are generated by non-domestic buildings; sustainable building refurbishment can play an important role in reducing carbon emissions. This paper looks at the performance of a recently refurbished 5-storey office building in London, in terms of energy consumption as well as occupants’ satisfaction. Pre- and post-occupancy evaluation studies were conducted using online questionnaire surveys and energy consumption evaluation. Results from pre-occupancy and post-occupancy evaluation studies showed that employees, in general, were more satisfied with their work environment at the refurbished building than with that of their previous office. Employees’ self-reported productivity improved after the move to the new office. These surveys showed a positive relationship between employees’ satisfaction with their work environment and their self-reported productivity, well-being and enjoyment at work. The factor that contributed to increasing employee satisfaction the most was: better use of interior space. Although the refurbishment was a success in terms of reducing energy consumption per m2, the performance gap was almost 3 times greater than that estimated. Unregulated loads, problems with building control, ineffective use of space and occupants’ behaviour are argued to be reasons for this gap. Keywords: Post occupancy evaluation, Refurbishment, Energy-saving, Occupants’ satisfaction, Space utilization
1. Introduction In the UK, non-domestic buildings account for approximately 18% of the carbon emissions in the UK (Carbon Trust 2009). The majority of non-domestic buildings in the UK were built
1
Research Engineer; Halcrow (CH2M Hill); London, UK;
[email protected]. Director Rail Civil Engineering; Halcrow (CH2M Hill); London, UK;
[email protected]. 3 Senior lecturer; Construction management; University of Reading; Reading,
[email protected]. 4 Professor, Psychology, University of Reading, Reading, UK,
[email protected]. 5 Registered Occupational Psychologist (HPC),
[email protected] 2
UK;
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before the 1980s, and more than half of all office space in the UK was built prior 1939 (Femenias and Fudge 2008). The age of the UK non-domestic stock indicates that for the country to meet its 80% CO2 reduction target by 2050, refurbishment of existing buildings will play an important role. Building refurbishment could also provide a more satisfactory work environment for the occupants, and, therefore, could improve productivity. This is explained in more detail in the following sections.
1.1 Work environment and employees’ satisfaction The ‘habitability pyramid’ developed by Vischer (2005) incorporates three groups of interrelated factors associated with employees’ comfort in a workplace: physical, functional and psychological. According to Vischer (2005), all three groups need to be considered if a comfortable and productive workplace is to be provided. ‘Physical comfort’ includes the satisfaction of all basic human needs, which ensures one’s health and safety; while ‘functional comfort’ concerns those features of the workplace that can help employees to perform their job well. ‘Functional comfort’ includes adequate lighting, flexible and adaptable furniture, designated spaces for different types of tasks, etc. ‘Psychological comfort’ involves feelings of ownership and control over one’s environment. It is usually assumed that employees who are more satisfied with the physical conditions of their workplace are happier and, therefore, are more productive than those who are less so (Leaman and Bordass 1999). Earlier studies indicate that there is a positive correlation between occupants’ satisfaction and their perceived productivity (Leaman and Bordass 2001; J. C. Vischer 2007; Thomas 2010). These studies confirm the importance of improving physical features of workplaces, such as air quality, lighting, noise, and temperature and office layout. In a recent study, Thomas (2010) revealed that increasing daylight, glare control, noise management and access to the windows (views) increased occupants’ satisfaction with their work environment.
1.2 Energy consumption assessment: Post-occupancy evaluation The results from the PROBE (Post Occupancy Review of Buildings and their Engineering) studies, which reviewed post-occupancy of 23 buildings, showed that actual energy consumption in buildings is typically 2-5 times more than predicted at design stage (Menezes 2012). This is partly due to the fact that several sources of energy usage are not considered in the calculations of design targets. These sources are known as unregulated loads and include IT equipment, server rooms, external lighting and lifts. Unregulated loads accounted for more than 30% of the total energy consumption in an office building (Menezes 2012). In addition to unregulated loads, there are various other factors which can affect the accuracy of energy consumption predictions. Occupants’ behaviour is one of these factors and, as this is often itself unpredictable, designers have to make assumptions about it (De Wit 1995).
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This paper presents lessons learnt from a post-occupancy evaluation (POE) of Halcrow’s recently refurbished HQ in London.
1.3 Background Halcrow (a CH2M Hill company) delivers planning, design and management services for developing infrastructure and buildings worldwide. In September 2010, Halcrow employees from the previous HQ, Vineyard House (VH) moved to the newly refurbished global headquarters (HQ), Elms House (EH). The poor environmental performance of VH, as well as its rigid and ineffective layout, generated the need for a new workplace. Halcrow decided to refurbish EH, which is located adjacent to VH (See Figure 1) and shares a common landlord with it, to be its new HQ building. The main objectives of the refurbishment were to reflect a sustainable design and create a flexible and active work environment with appropriate spaces for different tasks. In this project, the design target for CO2 emission was calculated to be 37 kg CO2/m2. This figure did not include unregulated loads. EH (marked with a circle in Figure 1) was completely stripped out and refurbished in 2010 and achieved a BREEAM rating of “Very Good” for its design. The key features of these two buildings are briefly described below.
Figure 1: VH and EH locations
1.3.1 VH VH is a 5-storey office building built in 1962, with a 5202.6m2 floor area. When Halcrow’s HQ, it was mainly open-plan, with few cellular offices and few formal meeting rooms with video conferencing facilities. There was a high level of lighting available at VH from both daylight and artificial (mainly fluorescent tube) sources. Although mechanical ventilation was available, because of the poor performance of the system, employees had to open the windows to get fresh air and, therefore, due to the location of the building, many employees were affected by the noise from the street. VH was heated by gas fired boilers via radiators throughout the building. These were complemented by portable heaters supplied to
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individual members of staff. A small canteen was located on the ground floor. About 479 employees were working at VH in 2009. 1.3.2 EH EH is a 5-storey office building which was built in the 1930’s with a floor area of 11,725m2. The offices are designed to be completely open plan with a number of small and large meeting rooms equipped with teleconferencing and video conferencing facilities. There are a number of designated areas for socialising and informal meetings as well as areas for concentration and contemplation; phone booths are available on each floor. A 60-seat restaurant is located on the ground floor, as well as kitchens on each floor. Facilities for cyclists are good, and include 6 showers. The office is mechanically air conditioned by use of fan-coils. A high level of lighting, from both natural and artificial sources, is available. The lighting system incorporates both daylight and PIR sensors to save energy. Half-hourly meters and electricity sub-meters are in use to monitor the energy consumption of the building accurately. Services at EH are mainly centrally controlled by a BMS system and the employees do not have control over their immediate environment. In 2011, 596 employees were working at EH.
2. Research approach In this research, Post-Occupancy Evaluation (POE) was employed to evaluate the refurbishment project’s success in terms of energy consumption, employees’ satisfaction and employees’ self-reported productivity. Surveys, observations, energy monitoring and benchmarking were used as research tools for this study. The actual performance of the building was compared to the UK’s benchmark as well as to the design target. The results were used to identify areas for potential improvements. There are different energy benchmarking tools available in the UK, such as CIBSE Guide F, ECON19 and CIBSE TM22. In this paper, ECON19 was used as a standard benchmark. For air-conditioned, prestige offices, the benchmarks are:
o o o
Good practice: fossil fuels: 114 kWh/m2 electricity: 234 kWh/m2 CO2 emissions: 143.4 kg CO2/m2
o o o
Typical: fossil fuels: 210 kWh/m2 electricity: 358 kWh/m2 CO2 emissions: 226.1 kg CO2/m2
The pre- and post-occupancy survey questionnaires used in this study were designed by the researcher to cover those workplace environmental factors identified as important influences in past studies (e.g., air quality, indoor temperature, noise level, outside view, personal control,
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visual privacy, auditory privacy, office layout, office appearance, cycling facilities, on-floor kitchen, recycling facilities). The questionnaire, which took under 15 minutes to complete, comprised three parts. There were 17 demographic items, 38 satisfaction items and 16 items concerned with sustainability awareness. In the “demographic” section, occupants were asked to indicate their age group, gender, the floor and building occupied, employment status, office type, frequency of visiting the in-house restaurant and frequency of using the shower facilities. There were 3 groups of ‘satisfaction’ items, pertaining to: physical environment, interior use of space and indoor facilities. In the “sustainability awareness” section, occupants were asked whether they knew about their company’s environmental sustainability targets and whether they felt personally responsible for meeting these targets. They were also asked to indicate what they considered to be the best method of communication for raising sustainability awareness within the building. Responses to the “satisfaction” items were sought on a 5-point scale, where 2= Strongly Agree, 1= Agree, 0= Neither Agree nor Disagree, -1= Disagree and 2 = Strongly Disagree. Most questions were positively worded; scores were reversed for negatively worded items. Analysis of the responses yielded mean values (a positive score indicating agreement with a positive statement) which allowed comparison between preoccupancy (benchmark) and post-occupancy values. The pre-occupancy online survey was carried out at VH in June 2010. The link to the survey, which stayed open for two weeks, was sent out to all employees at VH. This benchmark survey was used as a tool to enable the employees to confidentially express how they felt about their work environment. A full year’s (2009) electricity and gas consumption data were also collected at VH. These data were used as benchmarks against which to evaluate EH’s performance. The post-occupancy survey was conducted at EH in February 2011 to measure any changes in employees’ level of satisfaction with their work environment 6 months after the move. At the same time, observations were carried out by the author to assess two areas: interior space usage and occupants’ behaviour towards energy saving. A full year’s (2011) energy data were collected at EH to evaluate the energy consumption of EH in comparison with that of VH and the benchmarks.
3. Results and Discussion The data gathered from the pre- and post-occupancy surveys and the energy data provided useful pictures from VH and EH overall. The mean value of each variable from the pre-occupancy survey was compared with the postoccupancy survey. Where a mean value is quoted in this paper, number of respondents (N), standard deviation (SD) and the percentage of dissatisfied respondents (DS) are also stated.
3.1 Pre- and Post-Occupancy Surveys Having excluded data from ineligible participants, a total of 162 and 183 respondents completed the pre- and post-occupancy surveys respectively, generating a response rate of 32% and 31%, which were considered acceptable. In the post-occupancy survey, 66% of the
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respondents specified their previous workplace as VH; the other 34% indicated their previous workplace other than VH. In both surveys, the distribution of respondents across a number of demographic variables, including business group, employment status, and grade, mirrored well the actual distribution of all Halcrow’s employees; the sample is considered to be adequately representative. 3.1.1 Work Environment Satisfaction The scale reliability of responses to the 28 ‘satisfaction’ questions (overall) was assessed for VH and EH; Cronbach’s alpha was found to be 0.91 and 0.92 respectively, indicating excellent reliability. The results confirmed that VH, with overall satisfaction mean score of -0.29 (N= 141, SD=0.50, 36%DS), had a poor workplace environment. Respondents at EH were statistically significantly more satisfied with their work environment, 0.39 (N=153, SD=0.52, 5.2%DS) than those in VH, t (292) =11.54, p
