Copenhagen. The performance optimization was achieved with different tools: EnergyPlus, jEplus and jEplus+EA. The experiment allowed the evaluation and.
Proceedings of BS2013: 13th Conference of International Building Performance Simulation Association, Chambéry, France, August 26-28
COMPARISON OF CONVENTIONAL, PARAMETRIC AND EVOLUTIONARY OPTIMIZATION APPROACHES FOR THE ARCHITECTURAL DESIGN OF NEARLY ZERO ENERGY BUILDINGS
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Proceedings of BS2013: 13th Conference of International Building Performance Simulation Association, Chambéry, France, August 26-28
Table 1 Main energy design strategies and features of Autarki List of possible Strategies
Implemented Design Features in Autarki 1:1
Figure 1 Autarki form studies: the high compactness is the common denominator of all the proposed and tested schemes Data monitoring and actual performances
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Proceedings of BS2013: 13th Conference of International Building Performance Simulation Association, Chambéry, France, August 26-28
Parametric studies
Table 2 Description of the simulated parametric variables Variables tested
N°
Figure 2 View of the prototype few steps before its completion
Total Of Simulated Design Alternatives
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139,968
Selected Parameters
Proceedings of BS2013: 13th Conference of International Building Performance Simulation Association, Chambéry, France, August 26-28
Figure 3 The naturally ventilated air-to-air heat exchanger
Performance Optimization
Figure 4 The path toward a nearly Zero Energy Building is described in few adjustments of the prototype
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Proceedings of BS2013: 13th Conference of International Building Performance Simulation Association, Chambéry, France, August 26-28
2
Yearly Cooling Energy needs (kWh/m )
80
60
40
AUTARKI after optimization Floor Boundary Ground Wall Insulation 0.434 m Roof Insulation 0.434 m Overhang depth 1.65 m Thermal mass 0.1 m Floor Insulation 0.334 m Exchanger Ins. 0m Vent Schedule Summer on People 3 Equipment gains 30 W
AUTARKI today Floor Boundary Wall Insulation Roof Insulation Overhang depth Thermal mass Floor Insulation Exchanger Ins. Vent Schedule People Equipment gains
Heating 2 5.4 kWh/m Cooling 1.65 kWh/m2
Heating 98 kWh/m 2 Cooling 0.6 kWh/m2
Outdoors 0.334 m 0.334 m 1.1 m 0m 0.334 m 0m On 1 30 W
20
0 0
20
40 60 2 Yearly Heating Energy needs (kWh/m )
80
Scenario-by-scenario with EnergyPlus
jEplus+EA - 60 generations
jEplus parametric simulation
jEplus+EA - 135 generations
100
jEplus+EA - 5 generations
Figure 5 Energy needs comparison: scenario-by-scenario with EnergyPlus, jEplus parametric simulation and evolutionary algorithm with jEplus+EA
50
Time (hours)
37,5
25
12,5
Energy Model(s)
Parametric Configuration
Job Execution
Results analysis
Total time
Scenario-by-scenario with EnergyPlus (10 cases, 2-cores)
jEplus+EA - 60 generations (139,968 cases, 10-cores)
jEplus parametric simulation (139,968 cases, 256-cores)
jEplus+EA - 135 generations (139,968 cases, 10-cores)
jEplus+EA - 5 generations (139,968 cases, 10-cores)
jEplus+EA - 60 generations (139,968 cases, 2-cores)
Figure 6 Time comparison: scenario-by-scenario with EnergyPlus, jEplus parametric simulation and evolutionary algorithm with jEplus+EA
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Proceedings of BS2013: 13th Conference of International Building Performance Simulation Association, Chambéry, France, August 26-28
Architect-Friendliness of Evolutionary Optimization
Time efficiency of evolutionary optimization
Assessing the Efficiency of Evolutionary versus Parametric Optimization
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Proceedings of BS2013: 13th Conference of International Building Performance Simulation Association, Chambéry, France, August 26-28
Figure 7 Efficiency of the different methods seen from an architectural process perspective
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Proceedings of BS2013: 13th Conference of International Building Performance Simulation Association, Chambéry, France, August 26-28
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