S2

World Sustainable Energy Days 25 - 27 February 2015, Wels/Austria Young Researchers’ Conference

Energy efficiency in schools by applying new mechanical ventilation requirements

Background

Diogo Costa da Silva MSc Mechanical Engineering | TDGI | [email protected]

I. New occupancy conditions & amount of time indoors, »» rise quality standards and better comfort conditions based in control strategies using mechanical systems;

Luísa Dias Pereira PhD Candidate, ADAI, LAETA – DEM, Univ. Coimbra | [email protected]

II. European Directive 2002/91/CE »» reducing energy consumption in the buildings »» 3 Decree-laws in 2006 (PT national legislation); EPBD (recast) 2010/31/EU »» SCE 2013 revison (PT national legislation);

Nuno Correia MSc EfS | ADAI, LAETA – DEM, Univ. Coimbra | [email protected]

III. New HVAC projects were designed prescribing fresh air flow through tabulated values »» 2 case studies: pre-primary and primary school + secondary school.

Night cooling simulation

Method

Tested as cooling strategy S1 - June & July

# Nighttime fans working periods definition (by anticipating the operation time 2, 4 & 6h) + night operation shifts of 2 & 4 h, stopping at 6:00 am (attending ≠ electricity tariffs);

Energy Consumption 2 Schools Simulation By New Rates of Fresh Air ≠ Methods Prescriptive + Analytical

# Fresh air flow rates were increased 10%, 15% & 20%, facing the initial value. # The effect on thermal comfort conditions was addressed through the PPD index

The schools’ building models

Two phase study: global approach (model construction & 1st energy consumption estimation/ disaggregation) + the hypothesizing of energy efficiency measures by simulation

S1: Mechanical Night Cooling S2: Model calibration w/ real data consumption

# The windows distribution (S1) was simplified, but glazing area/room was respected

# S1 Longitudinal section (original design project) and SE façade (simulated model). Table : General data of the 2 schools’ simulation models

School S1 S2

Infiltration rate (h-1) 0,6 0,5

Temperature set point (ºC) Winter Summer 20 25 20 25

Efficiency Heating* 0,8 4,1

Ventilation (%) 80 80

Calculation method I – Prescriptive

Note*: For S1 it was admitted a global system efficiency (boiler and pipe loses) of 80%. For S2 the nominal datasheet COP was used. Note**: For S1 it was used the default value of the Portuguese legislation (ERR=3). For S2 the nominal datasheet ERR was used.

# Tabulated values for ≠ activities & spaces, the legislation prescribes the fresh air flow rate (per occupant & area of space)

# 2yrs electricity bills compared w/ the simulation

# The values intend to ensure the dilution of pollutants (due to occupants) & takes into account the pollutant load of the building, calculated as a function of the type of activity Design conditions (2007 legislation [11] ) m3/h.occ h-1 30 4,30 5 1,68

Space Classroom Corridors

𝑖

# Applying the equations 𝑀𝑚𝑒𝑑 =

Prescriptive method (2013 legislation [13]) m3/h.occ h-1 24 3,44 2 0,67

𝑁𝑀𝑖 .𝑀𝑖 𝑖

𝑁 𝑀𝑖

# Energy disaggregation: HVAC = 36.5%

Analytical method (2013 legislation [13]) m3/h.occ h-1 19 2,72 2 0,67

Results & Discussion

𝑄𝐴𝑁

𝑄𝐴𝑁

.𝑒

Room Electricity [kWh] Heating [kWh]

7%

Cooling [kWh]

9%

Bathrooms exhaust air ventilation [kWh] Exhaust and supply air ventilation [kWh]

# S2 model’s annual electric consumption disaggregation (kWh)

 Prescriptive method (PM) | New Q values »» 36.2% of the total primary energy (TPE) in heating & ventilation systems

# S2 base simulation »» HVAC = 36.5% total energy consumption. Lighting = 1/3 electricity consumption »» daylighting potential testing  Illuminance sensors »»» 5% reduction of annual energy consumption  Payback estimation period of 17 sensors (1/classroom) = 2 yrs & 7 months

# The following formulas are used: + 𝐶𝑖𝑛𝑡 𝑡𝑖−1 − 𝐶𝑒𝑥𝑡 −

32%

 3rd simulation, considering a cooling system »» 13.3% reduction of TPE up to 20% (AM)

# Real or predicted occupancy profile, calculating the fresh air flow, considering the time evolution of the bioefluents emission, to allow CO2 average < 1250ppm

(1) 𝐶𝑖𝑛𝑡 𝑡𝑖 = 𝐶𝑒𝑥𝑡 +

0%

 Analytical method (AM) | New Q values »» 40% reduction of TPE

Calculation method II – Analytical 𝑄 − 𝐴𝑁 . 𝑉

20%

# S1 first simulation = baseline energy consumption definition

& 𝑄𝐴𝑁 = 𝑀𝑚𝑒𝑑 . 𝑄𝐴𝑁,1𝑚𝑒𝑡 in a typical classroom

𝐺𝐶𝑂2

Lighting [kWh]

32%

(25 stud +1 teacher), QAN becomes 624 m3/h vs 975 m3/h estimated in the project phase

𝐺𝐶𝑂2

# Model vs real consumption data 0.5% deviation

Cooling** 3 3,66

 PM = 28% reduction infiltration rates »» 7% reduction annual energy consumption AM = 42% reduction infiltration rates »» 12% reduction annual energy consumption

𝑡𝑖 −𝑡𝑖−1

(2) 𝐺𝐶𝑂2 = 17000. 𝐴𝐷𝑢 . 𝑀 . 𝑁

Prescriptive Meth.

where: t - time instant [h]

Analytical Meth.

Base simulation

Q project value

Cint (ti) - CO2 concentration indoors in the instant ti, [mg/m3] QAN - Fresh air flow rate,

(2006 legislation) Q prescriptive method value

[m3/h]

(2013 legislation) Q analytical method value

Cext - Outdoor concentration of CO2, [mg/m3]

(2013 legislation)

𝐺𝐶𝑂2 - Emission rate of CO2 inside the compartment, [mg/h] V - Volume of the compartment, [m3] 𝐶𝑖𝑛𝑡 𝑡𝑖−1

- Initial concentration of CO2, [mg/m3]

# S2 fresh air flow rates calculations (resultant of the ≠ legislation & methods)

# S2 energy consumption estimations (resultant of the ≠ legislation & methods)

# In (2) the emission rate of CO2 is calculated considering the number of occupants in the space and the Dubois (Adu) of the considered occupant

Examples

S2 : 2 AHU w/ heat recover for each module of 4 buildings (1 per level)

Discomfort # S1 Results of the percentage distribution of the comfort conditions (no. hours night mechanical cooling/ categories)

S1 : No cooling system. Centralized heating system

Conclusions & Outlook  The night cooling ventilation strategy does not show to be effective for reduction of energy consumption, but it has a significant impact in the occupants’ thermal comfort;  HVAC systems represent a very significant part of the schools’ energy consumption;  The fresh air flow rate (Q) has a decisive nature in the HVAC energy aspect – it showed to be of greater influence in the final energy consumption;  The new legislation ventilation requirements’ revealed a potential reduction on the

School

# Map of Portugal highlighting the 2 schools’ location; Axonometric views of the school models. Above: School S1 - level 0 (left) and level 1(right); below: School S2– rooms’ distribution (level 1).

Nº students

S1

375

S2

1100

Age (y) 3-6 (75) 6-10 (300) 11-18

TPE consumption of more than 30% in the heating and ventilation components;  The AM has shown an energy saving potential 5% over the PM;  Properly dimensioning & selecting the ventilation equipment/system is an important contribution to more sustainable school buildings »» reduced energy consumption &

School S1 S2

Area (m2) Ceiling height (m) 3043 5052

3,7 3.74 – 4.04 – 4.74

External Walls Isolation U Position W/(m2.ºC) Outside 0.47 Outside 0.48

Roof U W/(m2.ºC) 0.59 0.62

Glazing Solar factor 0.26 0.56

U

U W/(m2.ºC) 1.64 2.84

C

correspondent GHG emissions;  If the new ventilation requirements are applied to other buildings’ types, e.g. the tertiary sector, higher energy consumption savings will occur among other public buildings.