A Hybrid Algorithm Based on Computational Intelligence Methods for Long-Term Household Electricity Consumption Management by Taking Economic Goals

The increasing of electricity consumption and future demand is one of the major issues of power companies around the world, and smart grid is one of the best solutions to the outage of this problem. Smart grid aims to solve problems existing power grids and better and more efficient power system management is raised. This paper presents a novel long term energy management approach based on genetic algorithm and PSO algorithm, suitable for implementation in the smart grid context. The main purpose of this paper is to present a method for determining effective investing in the domestic appliance optimization, aim to reducing energy consumption in the household sector. The first step toward achieving these goals is the providing a model for appliance efficiency rate. This model is used for investment optimization in a variety of appliances and its effect on household power consumption. In the second step, a cooperative game with transferable utility is used for modeling the coalition of special items which customer is willing to more invest in them, such as basic appliances. The purpose of this step is to increase the possibility of the presence of these appliances in the consumption management program. Finally to solve the problem has proposed a hybrid tool based on PSO algorithm and genetic algorithm. The simulation results represent 45.56% of electricity consumption reduction and 80.48% of repairs cost reduction. The outcomes prove that the proposed hybrid algorithm is an efficient and effective tool to solve the long-term household electricity consumption management problem.