Economic Optimal Scheduling of Microgrids Based on IPM Real-coded Genetic Algorithm
With all kinds of distributed energy access to the microgrid,to the microgrid operation stability caused by certain impacts at the same time,but also to the microgrid economic scheduling has brought great challenges.In order to address the economic scheduling problem of microgrids containing distributed energy and energy storage systems,this paper firstly establishes generation unit and load models according to the structure of distributed energy grid-connected microgrids,and then establishes an economic optimization scheduling model with the objective func-tion of minimizing the total cost of microgrids and the quality coefficient of electricity consumption by taking into ac-count the constraints such as power balance of the power system,power sales,the amount of transferrable loads,and the SOC of the energy storage system.In order to improve the model solving accuracy,finally,an IPM genetic algo-rithm is proposed to improve the crossover factor and mutation factor.The simulation results show the effectiveness of the proposed algorithm to accelerate the convergence of the objective function and improve the microgrid scheduling economic.
万方数据
维普
