Volume 04: Proceedings of 11th International Conference on Applied Energy, Part 3, Sweden, 2019

Home Energy Management System Based On Improved Genetic Algorithm And Multi-objective Function Xin ZHAO, Xiangyu KONG, Yongxing TENG, Ye LI, DeLong DONG


In order to realize the economic operation of the home energy management, the electricity cost of user needs to be reduced and user-side satisfaction should be improved. A home energy scheduling optimization model including the home electricity load model and the photovoltaic power generation model was constructed, the objective function was established, which takes minimizing the electricity cost and the user satisfaction into consideration. With the constraints of power balance, load working time and temperature control load. Finally, combining genetic algorithm with local optimization method, a hybrid Pareto genetic algorithm for multi-objective optimization is proposed to obtain the approximate solution of multi-objective function. Based on the simulation results of MATLAB platform, the optimal solution which both minimizes electricity cost and maximizes user’s satisfaction has been obtained.

Keywords House energy management, Genetic algorithm, Multi-objective function, Optimization

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