Optimization of Daylight and Energy performance of residential buildings Using Genetic Algorithm in Hamedan

The present study evaluates and optimizes daylight and energy performance of residential buildings in the cold climate of Hamedan. For this purpose, the common pattern of residential buildings in Hamadan city, which has 5-storey residential apartments with eastern and western neighborhoods and as a result of lighting on the north and south, was selected as the base model and annual energy consumption and utilization of natural light were considered as the objective functions. After examining the methods used and the various metrics of daylight and energy performance evaluation, annual energy consumption per unit area (EUI) to evaluate the amount of energy consumed, and daylight illumination (UDI) for assessing the utilization of natural light were selected to find optimum solutions for the design of the main envelope of residential buildings. Then, various components of the envelope of residential buildings were identified; following that the sensitivity analysis was performed using Morris screening method in order to rank the key variables affecting the objective functions. Further, parametric studies on output variables and optimization of solutions were considered using genetic algorithm. Thus, Based on the interaction between the simulation software and the multi-objective optimization method, a number of Pareto optimal solutions were produced that through comparing them with consideration of both aspects of energy and daylight, optimal design was selected. The results show that through Pareto optimization in selected patterns, 17.44% and 23.72% of the EUI metrics and 17.61% and 21.1% of the UDI metrics can be improved. Accordingly, the design of the building envelope in this way can greatly reduce energy consumption and, at the same time, increase the efficiency of natural light.