Optimization of Energy Consumption of Residential Buildings Using Genetic Algorithm

In this study, the amount of energy cost savings for a period of ten years has been calculated using the P_1-P_2 method, which is one of the economical methods of energy life cycle insulation analysis. This method is one of the most popular and practical methods available to calculate the cost of energy savings as well as the thickness of thermal insulation for long periods of time. In this research, genetic algorithm method has been used for optimization. In a genetic algorithm, each optimization variable is a gene, and the combination of all the optimization variables together forms a chromosome. Finally, the results of energy saving for the optimal insulation thickness over a period of ten years using the P_1-P_2 method for the four heating and cooling systems for insulation only and insulation mode considering the reduction of system size in Tehran using The method of optimizing the genetic algorithm is investigated. In this study, the amount of energy cost savings for a period of ten years has been calculated using the P_1-P_2 method, which is one of the economical methods of energy life cycle insulation analysis. This method is one of the most popular and practical methods available to calculate the cost of energy savings as well as the thickness of thermal insulation for long periods of time. In this research, genetic algorithm method has been used for optimization. In a genetic algorithm, each optimization variable is a gene, and the combination of all the optimization variables together forms a chromosome. Finally, the results of energy saving for the optimal insulation thickness over a period of ten years using the P_1-P_2 method for the four heating and cooling systems for insulation only and insulation mode considering the reduction of system size in Tehran using the method of optimizing the genetic algorithm is examined.