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3rd International Exergy, Life Cycle Assessment, and Sustainability Workshop & Symposium (ELCAS3) 07 - 09 July, 2013, NISYROS - GREECE

GREEN ENERGY SOLUTIONS AND CITIZENS’ PARTICIPATION IN ENERGY PLANNING AND MANAGEMENT: A CASE STUDY FOR BASILICATA REGION S. Di Leo a, C. Cosmi a, F. Pietrapertosa a, M. Salvia* a, M. Caponigro b, F.Giornelli b, F. Leopaldi b, P. Motta b a

National Research Council of Italy - Institute of Methodologies for Environmental Analysis (CNR-IMAA) C.da S.Loja 85050 Tito Scalo (PZ), Italy Email: [email protected], Email: [email protected], Email: [email protected], Email: [email protected], b

DeMEPA (Design and Management of Electrical Power Assets), Via Madrid 16, 2090 Segrate (Milano), Italy Email: [email protected], Email: [email protected] Email: [email protected] Email: [email protected]

Abstract Energy system sustainability represents one of the major challenges that Europe, National Governments and Local Authorities are facing in order to achieve their economic, social and environmental objectives. The Energy and Climate European policy, the SET-Plan and other directives (e.g. Directive 2009/28/EC on the promotion of energy from renewable sources) have boosted large investments in renewable energy technologies. This is particularly true in Italy where economic incentives supported by national laws brought, in 2011, the setting up of about 9000 MW of new PV plants and 7000 MW of Wind plants. The increasing supply of intermittent sources in the electrical power system has important consequences on the system management. In particular, electrical systems must be enabled to manage and balance a discontinuous power production (such as Wind and PV) with fossil production and storages. In this framework micro-grids can play a key role in the transition towards smart and active energy systems, providing for a more efficient configuration through consumers and businesses engagement and allowing the valorisation of the endogenous resources. The paper presents the first results of an ongoing research concerning the introduction of microgrids technologies in a regional framework (the Basilicata Region, Southern Italy), jointly carried out by CNR-IMAA and DEMEPA. The achievable benefits in term of energy efficiency have been evaluated by an integrated modelling platform, the TIMES-Basilicata model, with the aim to provide policy-makers, planners and researchers for feasible solutions, replicable to other geographical areas interested by a noticeable increase of renewable energy sources.

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Keywords: Energy System Analysis and Modelling, Micro-Grids, Renewable Energies, Regional Energy Planning.

1. Introduction The “Roadmap for moving to a competitive low-carbon economy in 2050” (see e.g. [1]) sets out a cost-efficient pathway to reduce domestic greenhouse gas emissions by 80% by 2050, introducing two intermediate reductions targets, 40% by 2030 and 60% by 2040. Meeting these ambitious targets requires strong efforts in all the main sectors responsible for greenhouse gas emissions, adopting resource efficient technologies and processes for moving to a competitive low carbon economy. In the different pathways explored by the Commission, electricity plays a central role in a low carbon economy paradigm through a reduction of gross demand, the electrification of heating and transport and the decarbonisation of the electricity supply (see e.g. [1]). To this end renewable generation (Wind, PV, Biomass, Hydro), that are increasingly competitive with fossil generation, can represent a feasible solution. Incorporating small- and medium-scale renewable electricity generation requires a careful management of current systems that were designed for large scale thermal, hydro or nuclear plants. In spite of the old ‘predict and provide’ paradigm, where the supply pursues a predicted demand, the aim is to develop a ‘demand response’ model, in which demand follows available supply. In this framework demand-side resources are used to minimize the need for fossil fuel reserve generation (see e.g. [2,3]). Proto-smart grids, with distributed generation and demand response, are already being undertaken, in particular when renewable resources are largely available and it is necessary to limit the imports of expensive fossil fuel imports (see e.g. [4,5,6]). However, a thorough investigation is required to assess the effectiveness and feasibility of renewable electricity generation in order to consider it a valid and widely applicable alternative in local energy systems planning. (see e.g. [7,8,9]). This paper aims at evaluating the potential effects and benefits of introducing micro-grids in a regional energy system (the Basilicata Region, Southern Italy) characterized by a high presence of distributed renewable energy sources that can be further exploited in the near future (see e.g. [10]). In particular, the proposed methodological approach analyzes the benefits related to micro-grids implementation with an ad-hoc partial equilibrium model (the TIMES Basilicata) implemented by the CNR-IMAA research team. A scenario analysis was jointly performed with the experts of DEMEPA to investigate the energy system behavior over a predefined time horizon (2007-2030). The baseline configuration is compared with two scenarios that explore the effects of micro-grids introduction in the local framework. In the following, the scenario assumptions and the main results obtained by scenario are discussed.

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This study represents the first step of a more ambitious project in which the two research units with different backgrounds are facing with a unique multidisciplinary approach the different aspects (technical, economic, social and environmental) involved in energy production, distribution and use, with reference to consolidated international good practices. The final aim is to provide policy-makers, planners and researchers with an integrated platform to support decision-making as well as to offer feasible and replicable solutions for the territorial areas interested by a noticeable increase of renewable energy sources.

2. Micro-grid motivation A micro-grid is a semiautonomous group of generating sources and end-users that are installed and operating for the advantage of its members (producers, consumers, prosumers and communities) in compliance with environmental, social and sustainable growth requirements (see e.g. [11,12]). A micro-grid is an electrical power system including: generating sources (renewable and distributed energies, and if necessary, traditional power plants), loads (residential, commercial, industrial and public), storage systems (not always present), local electrical network (mainly in low-voltage) that connect the different sources and loads, an ICT infrastructure for the power system control and management (see e.g. [13,14]), a connection with the medium-voltage Macro Grid. Typical target applications for the Micro Grid business refer to small-medium applications of about 1000-3000 people (which represent about 20-25% of Italian municipalities) characterizing a customer structure with about 200-350 users/consumers, small commercial and industrial public utilities (schools, public lighting) and small distributed generation. The reduction of electrical losses in the transmission and distribution networks is the more evident advantage: in fact, the use of electricity in the neighborhood of the generation sites determines a higher efficiency, a decrease of pollutant emissions and financial resources savings. Other valuable advantages of the micro-grids installation are related to a consumer-based electricity supply: the possibility to correlate the tariffs applied to the micro-grid users with the required PWR (Power Quality and Reliability) of the supply (flexibility is not allowed on the large number of Macro Grid users) that leads to a favorable framework for the development of demand-side management actions,

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new jobs opportunities for technical graduates (engineers, informatics), technicians and specialized workers for the micro-grid O&M, enhanced social inclusion of the micro-grid users determined by a improved sense of belonging of the community that can be helpful in the territorial implementation of energy and environmental strategies. The micro-grids have also a positive impact on the Medium Voltage and High Voltage macro grids by: Decreasing the electrical congestion (bottlenecks) on the Medium and High Voltage networks and thus reducing the investments addressed to solve this crucial aspect, Decreasing re-powering investments of macro grids.

3. Methodological approach Many formal methods are available for the representation of energy systems and an indepth investigation of their behavior over a medium-long time horizon, with reference to key energy-environmental policy issues and technology advancements. The ETSAP-TIMES models’ generator, developed under the aegis of the International Energy Agency (see e.g. [15,16]), allows a bottom-up technology-oriented representation of energy systems and their exogenous boundary conditions (i.e. resources and technologies availability, legislative restrictions) generating multi-period demand-driven optimizing models that are currently utilized in many countries for scenario analysis at different spatial scales. The TIMES-Basilicata model, properly developed with the aim to represents the energy system of Basilicata Region over a 33-year time period (from 2007, the reference base year, to 2030), allows representing energy flows from supply to end-use demands through the network of technologies, including both fossil and renewable energy vectors. The energy system’s evolution over the time horizon is described starting from a statistical reference year by introducing key data and constraints in the multi-period structure. An user’s interface system (see e.g. [17,18]) allows managing the input data (resources availability, technical, economical and environmental features of technologies, exogenous constraints), generating the partial equilibrium model matrix to be fed into the model’s solver and analyzing the model outputs. The model individuates the minimum-cost solutions by scenario and defines the optimal levels of utilization of resources and technologies that accomplish the system’s constraints and scenario assumptions. The results are usually aggregated into thematic tables and post-processed to investigate the trends of key variables (such as primary energy and final energy by sector and / or by fuel, electricity generation mix, imports, exports and domestic production of fossil and renewable fuels, total and annual energy system costs, investment costs, etc.).

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The supply sector includes mining of primary resources, import and export of primary fuels and electricity production, with a particular focus on electricity production and distribution sub-systems. All in-use traditional technologies are included in a Reference Energy System (RES) database whereas the new technologies with their relevant data and availability in the different time periods are enclosed in a so-called “sub-RES” database. As an example, Table 1 shows a list of technologies for electricity production with the main technical characteristics, investment and O&M costs. Table 1: Technologies for electricity production Efficiency

Gas turbine < 80 MW Gas turbine< 300 MW Combined cycle (turbogas) < 3000 MW Cycle with steam turbine>500 MW – coal Cycle with steam turbine with CO2 sequestration IGCC Coal with CO2 sequestration Steam turbine < 2500 MW - fuel oil Wind plants Off-shore wind plants Biomass plants Mini hydraulic< 1 MW Mini hydraulic >1 MW Photovoltaic plants (roofs ) Photovoltaic plants (multi MW) Biogas Agriculture-Livestock

Life (years)

Investment (M€/GW)

O&M costs (M€/GWh) 0,0027 0,0020 0,0020

0,350 0,336 0,460

25 25 30

0,277 0,160 0,550

(M€/GW) 0,0085 0,0085 0,0123

0,440

35

1,100

0,022

0,0011

0,400

35

1,600

0,0345

0,0011

0,460 0,432 0,300 0,300 0,250 0,800 0,800 0,150 0,150 0,300

35 40 15 15 15 30 30 20 20 9

1,420 0,969 1,700 2,800 2,350 4,500 3,500 6,000 5,000 3,500

0,065 0,0226 0,0350 0,0600 0,0750 0,0780 0,0330 0,0500 0,0500 0,0750

0,0036 0,0011 0 0 0,0040 0 0 0 0 0

The analyzed demand sectors are Residential, Commercial, Industry and Agriculture. Residential and Commercial are described in full details whereas Industry and Agriculture are modeled in a more aggregate way (“black-boxes”). The electricity distribution network is modeled considering four voltage lines: Very HighVoltage, High-Voltage, Medium-Voltage and Low-Voltage, each one characterized by different parameters in terms of transmission efficiency, investment and O&M costs. The model is calibrated to the year 2007, based on TERNA data (see e.g. [19]) and the Basilicata Region Energy Plan (see e.g. [20]) information, being the electricity generation represented in Table 2. Table 2: Electricity production in Basilicata Region and relevant losses in transmission and distribution networks Electricity generated

GWh

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Hydroelectric plants Thermoelectric plants Wind plants Photovoltaic plants

227,1 1048,6 261,7 0,5

Total electricity generated

1537,8

Import from other regions

1624,9

Losses

231,6

The micro-grid concept was introduced into the model by reducing the transmission and distribution losses for the electricity generated into the micro-grid, keeping unchanged all the other parameters characterizing different generating sources (capital costs, O&M costs, efficiency). In this preliminary investigation, the costs of micro-grid setting up was not taken into account in order to assess the differential impact of micro-grids in terms of increase of energy efficiency, as it is the key starting point for any subsequent economical and environmental analysis. Moreover there are several different critical aspects related to the setting up of micro-grids (e.g. the costs to be allocated for the purchase or rental of the existing distribution network used by the micro-grid) that will require a specific study on this step.

4. Result analysis In order to provide a sound basis of comparison, the first step dealt with the implementation of a Business As Usual (BAU) scenario for the Basilicata region energy system, characterized by the current energy trends and policies in use. Two alternative scenarios were then built up to evaluate the micro-grids contribution: the MICRO-GRID1 scenario in which all the photovoltaic plants characterizing the BAU scenario operate in micro-grids modality, and MICRO-GRID2 where, in addition to PV plants, co-generative gas turbines operating in micro-grids modality were included, taking into account the energy credits in terms of substitution of imported electricity. 4.1 BAU scenario The amounts of electricity generated over the time period 2010-2030 in the baseline configuration is represented in Figure 1.

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Figure 1: BAU scenario: Generation of electricity

It can be observed that the total electricity generated in the region increases from 2149 GWh (year 2010) to 2277 GWh (year 2030) in the investigated period, while the imported electricity decreases from 935 GWh (year 2010) to 351 GWh (year 2030). The decrease of imported electricity is due to: a reduction of the electricity consumption induced by the decrease of resident population: 577.562 inhabitants in 2007 and 531.495 inhabitants in 2030, according to the ISTAT (Italian National Institute of Statistics) forecast; a development of the renewable energy generated in the region as follows: o the wind plants contributes with 454 GWh in 2010 up to 796 GWh in 2030; o the PV production raises from 45,2 GWh in 2010 to 323 GWh in 2030. This sharp increase of RES sources contribution determines a significant reduction in the thermoelectric plant generation. The electricity flows in the High, Medium and Low Voltage networks over the period 2010 – 2030 are represented in Table 3.

Table 3: Electricity flows (GWh) in Basilicata Region networks 2010

2014

2018

2022

2026

2030

High Voltage

3001

2656

2374

2386

2232

2305

Medium Voltage

2523

2245

1990

2013

1876

1955

Low voltage

1427

1306

1149

1207

1158

1207

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The corresponding energy losses are shown in Figure 2: they are on average equal to 5,2%, 5,5% and 8,2% respectively for the High, Medium and Low Voltage networks.

Figure 2: BAU scenario: Energy losses in transmission and distribution networks

4.2 Micro-grid scenarios In the MICRO-GRID1 scenario all the photovoltaic plants are operated in a micro-grid framework: the corresponding generated electricity fulfils the electrical loads allowing a decrease in the network losses strongly dependent from the micro-grid topology (e.g. the distance between the plant and the loads). The following values have been assumed for the losses reduction:  0,5% at medium voltage and 0,8% at Low Voltage for the PV plants connected to the Medium Voltage network,  0,8% for the PV plants connected to the Low Voltage network. The decrease of electrical losses determines a corresponding decrease of the total electricity demand (with the same consumption) as reported in Table 4, in which the percentages of micro-grids generation is compared with the loss reductions. Table 4: Losses decreasing in regional networks compared to the amount of electricity generated in micro-grid 2010

2014

2018

2022

2026

2030

Electricity generated in micro-grid

1,5%

7,2%

8,8%

9,8%

11,6%

12,5%

Loss reduction in the region networks

1,4%

6,7%

8,1%

9,1%

11,0%

13,8%

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The decrease of energy demand leads to a reduction of imports with relevant benefits also on the national grid. Figure 3 shows the comparison of the total losses between BAU and MICRO-GRID1 scenarios.

Figure 3: Comparison of the total electricity losses between BAU and MICRO-GRID1 scenarios

In the MICRO-GRID2 scenario, co-generative gas turbines are operating in a micro-grid framework from 2014, with a yearly energy production equal to 138,1 GWh. The amount of electricity produced by the gas turbines nearly replaces the imports. The corresponding electricity produced over the investigated period is reported in Figure 4.

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Figure 4: MICRO-GRID2 scenario: Generation of electricity

The comparison between Figure 4 and Figure 2 underlines the significant changes in the mix generation of electricity fostered by an enhanced utilization of micro-grids. As expected, network losses, shown in Figure 5, decrease noticeably respect to the BAU scenario, ranging from 44 to 65 GWh respectively in the years 2014 and 2030.

Figure 5: Comparison of the total electricity losses between BAU and MICRO-GRID2 scenarios

5. Conclusion and further developments The scenarios analysis highlights the main advantages in terms of energy efficiency related to the installation of micro-grids, under the considered scenario assumptions: a decrease of transmission and distribution losses ranging from 12% to 20% (MICRO-GRID 2 scenario), a higher efficiency of the overall power system ranging from 1,7% to 2,5% respectively in the years 2014 and 2030. These results point out that the micro-grids could constitute a favorable structure for electricity generation from distributed sources, and in particular from renewables, replacing the electricity generated by fossil-fuel power stations. The results illustrated in this paper represent the first outcomes of a complex modeling process and micro-grids feasibility assessment that will be further analyzed under different scenario assumptions. In a near future the socio-economic component will be emphasized: in particular the financial aspects concerning micro-grid building and operation will be investigated taking into account the infrastructural, social and regulatory aspects. The economic data (investment and operating costs) will be therefore included in the TIMES-Basilicata model in order to explore the possible development of micro-grid solutions both in perspective

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analyses and for energy planning purposes as well as to support operatively the definition of future regional energy strategies.

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