Diapositivo 1
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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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