Multi-objective optimization of building energy performance using GA coupled with EnergyPlus: A case study in various climatic zones of Iran

In this paper a multi-objective genetic algorithm is coupled to a whole building energy simulation program to obtain the optimal solutions in order to promote the building energy performance. The scope of this study is to explore the effect of some architectural parameters including building orientation, window size and overhang specifications on the energy performance of building envelope in four climates of Iran. In the optimization section, multi-criteria optimization analyses of total annual cooling load and total annual lighting load are investigated with the aim of understanding the interactions between two mentioned objective functions. The optimal solutions from the multi-objective optimization problem are reported in the form of Pareto frontiers and finally the results of the multi-criteria optimization are compared with the EnergyPlus baseline model. The results show that for a typical model, the total annual cooling load may be reduced about 34.6 to 63.3 % by changing its specifications and increasing the total annual lighting load by about 0.79 to 2.4 %. It means that the architectural design parameters of building are important and critical in determining building energy consumption.

Keywords:

EnergyPlus , jEPlus , Genetic algorithms , Energy consumption , Multi-objective optimization