Transcript Diapositivo 1

Assessment of the Energy Savings Potential of
Daylight Utilization and its Impact on a Building
Energy Performance
Hermano Bernardo
Vienna, 2010
Energy efficiency in buildings – some challanges
 Reducing energy consumption and greenhouse
gases emissions
 Optimizing Heating, Ventilation and Air Conditioning
(HVAC) systems
 Optimizing artificial lighting systems:
 Maximizing the use of natural lighting
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Energy efficiency in buildings – some challanges
 Ensuring good indoor air quality (IAQ):
 Adequate ventilation with filtration
 Thermal comfort
 Evaluating the energy performance:
 Determining the energy efficiency classification
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Portuguese energy outlook
Transport
1%
Transport
38%
Industry
29%
Domestic
17%
Services
12%
Others
4%
Buildings:
29% of final energy
Industry
33%
Others
4%
Domestic
28%
Services
34%
Buildings:
62% of electricity
Source: DGEG, 2006
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Legal impositions
 European Directive 2002/91/EC: Energy Performance of
Buildings (EPBD)
 SCE - Sistema Nacional de Certificação Energética e da Qualidade do
Ar Interior nos Edifícios (Decreto-Lei n.º 78/2006)
 RSECE - Regulamento dos Sistemas Energéticos de Climatização em
Edifícios (Decreto-Lei n.º 79/2006)
 RCCTE - Regulamento das Características de Comportamento
Térmico dos Edifícios (Decreto-Lei n.º 80/2006)
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Portuguese regulations – application
 RCCTE
 Residential buildings;
 Small services buildings without central HVAC systems, or P ≤ 25
kW;
 Basis for the simplified methodology – certification of existing
buildings.
 RSECE
 Services buildings:
 Large (>1000 m2 or 500 m2);
 Small with HVAC (P > 25kW).
 Residential buildings with HVAC systems, P > 25kW
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Case study – Canteen Building
Location: Leiria
Climate zone: I2V1Norte
Main façade: SE
Year of construction: 2005
Element
U [W/m2.ºC]
External wall
0,50
Ground floor
2,50
Flat roof
1,60
Pitched roof
0,85
Glazing description
Double glazed aluminum
window (6+10+4) mm
U [W/m2.ºC]
3,74
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Methodology
 Development of a computational model of the building
 Model calibration
 Full energy audit
 Detailed characterization of the actual operating conditions of the building
 e.g. Occupation, equipments, lighting, temperature regulation...
 Simulation of nominal consumptions
 Using reference patterns, rather than actual occupation, equipments and
lighting profiles and densities
 A climate data file is needed
 Determination of the Ieenom index and assignment of the Energy Class
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Calculation of IEE index
Q aq
Q arr
Q out
IEE 
 FC I 
 FCV 
Ap
Ap
Ap
IEE – Energy efficiency index [kgoe/m2];
FCI – Correction factor for heating;
FCV – Correction factor for cooling;
Qaq – Energy used for heating [kgoe/year];
Qarr – Energy used for cooling [kgoe/year];
Qout – Energy used for other purposes [kgoe/ano];
Ap – Net floor surface [m2].
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Building energy simulation
 Set of parameters has to be defined:
 e.g. working hours diagrams for lighting, occupation, equipments, air
changes, ventilation equipments, heating and cooling temperatures
 Confort conditions:
 Heating season: air temperature of 20ºC
 Cooling season : 25ºC with 50% relative humidity
 Primary energy conversion factors
 0,290 kgoe/kWh for electricity
 0,086 kgoe/kWh for natural gas
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Building energy simulation
 Simulation tool – DesignBuilder for EnergyPlus:
 Climatic data;
 Definition of the geometry and thermal zones to be included in simulation;
 Building envelope characterization;
 Internal loads definition;
 Parameters of infiltration and ventilation systems;
 Environmental control definitions.
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Building model
Floor
Construction
surface [m2]
Net surface
[m2]
0
1.074
854
1
894
633
Total
1.968
1.487
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Model calibration
 Comparison between annual energy consumptions
Measured
consumption
Simulated
consumption
Deviation
[kgoe]
[kgoe]
[%]
Electricity
57.982
52.942
-8,7%
Natural gas
23.205
24.455
+5,4%
TOTAL
81.187
77.397
-4,7%
Energy type
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Base case simulation
Electricity
Thermal energy
Total
[kWh]
[kWh]
[kgoe]
Lighting
31.355
0
9.093
Equipments
144.314
54.177
46.510
Heating
0
55.587
4.780
Others
6.888
174.599
17.013
TOTAL
182.557
284.363
77.397
Energy usage
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Lighting systems optimization simulation
Electricity
Thermal energy
Total
[kWh]
[kWh]
[kgoe]
Lighting
23.494
0
6.813
Equipments
144.314
54.177
46.510
Heating
0
57.851
4.975
Others
6.888
174.599
17.013
TOTAL
174.696
286.627
75.312
Energy usage
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Comparison of results – primary energy
[kgoe]
Lighting
optimization
[kgoe]
Lighting
9.093
6.813
25,1
Equipments
46.510
46.510
0,0
Heating
4.780
4.975
-4,1
Others
17.013
17.013
0,0
TOTAL
77.397
75.312
2,7
Energy usage
Base case
Reduction
[%]
 Energy for lighting systems reduced in 25% but, due thermal load
reduction, energy for heating increased in 4%.
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Annual energy savings potential
Repercussion on
electricity
consumption
Repercussion on
natural gas
consumption
Energy
saving
[kgoe]
Cost
reduction
[€]
2.280
708
-195
[€]
Pay-back
time
[years]
~3.000
~5
Investment
-121
 Globally, there is an energy saving potential of 2.085kgoe, which
means a total cost reduction of 587€ and a reduction in CO2 emissions
of 3.172 kgCO2e.
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Energy labelling of the case study building
 Full simulations were performed under two scenarios:
 Reference case;
 Maximization the use of natural lighting.
Energy Class
Limits
A+
0
IEEnom
95,25
A
95,25
IEEnom
103,5
B
103,5
IEEnom
111,75
B-
111,75
IEEnom
120
C
120
IEEnom
136,5
D
136,5
IEEnom
153
E
153
IEEnom
169,5
F
169,5
IEEnom
186
G
186
IEEnom
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Reference case - with nominal profiles
Energy consumption
[kgoe]
Heating
Cooling
Others
35.217
20.078
113.001
IEE = 104,89 kgoe/m2
Class B
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Maximization of the use of natural lighting
Energy consumption
[kgoe]
Heating
Cooling
Others
36.049
19.737
106.411
IEE = 100,59 kgoe/m2
Class A
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Conclusions
 A lighting control system that maximizes the use of natural lighting
leads to a considerable reduction of the IEEnom index and the building
becomes a Class A building.
 During the winter, artificial lighting systems can be beneficial and
should always be taken into account when performing simulations and
sizing HVAC systems, as they represent a thermal load which
contributes to the building’s heating.
 During the summer, lighting systems should also be considered, this
time because they represent an extra load that must be removed by the
cooling system, in case of its existence.
 Computational simulation enables the comparison beforehand, in terms
of energy performance and thermal comfort, of different alternatives.
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