基于改进GSA-GWO算法的含分布式电源局部电网孤岛划分策略OA北大核心CSTPCD

In order to further improve the efficiency and reliability of the local power grid in the process of fault recovery,this paper proposes an island partition strategy of local power grid with distributed generation based on improved GSA-GWO algorithm.Firstly,the optimal-worst method is used to evaluate the load to obtain the load weight value,so as to determine the priority of island division of important load restoration under local power grid fault.Secondly,combined with the load priority,the load level weight coefficient is determined,and the objective function model of island division of local power grid with distributed generation is constructed.Then,in order to obtain better objective function solution results,chaotic reverse learning and genetic annealing algorithm(GSA)are introduced to improve the grey wolf optimization algorithm(GWO)to improve the optimization performance of the algorithm.Finally,the modified IEEE 69 node is taken as an example for simulation analysis.The improved GSA-GWO algorithm is used to solve the local distribution network fault model,and a better islanding result is obtained.The example analysis shows that the strategy proposed in this paper can accurately realize the optimal strategy of island division under local grid fault,ensure the restoration of power supply of important loads,and verify the effectiveness and superiority of the strategy.