Islanding partition method based on chaotic OPL-GWO algorithm under local grid fault

In order to further improve the efficiency and reliability of the local power grid in the process of fault recovery, the local power grid with high proportion of distributed generation is divided into islands based on the chaotic OPL-GWO algorithm. Firstly, the optimal-worst method is used to evaluate the load to obtain the load weight value, and the priority of important load restoration considering island partition under local power grid fault is determined. Secondly, the load priority is considered to determine the load level weight coefficient value, so as to construct the objective function model of island partition of local power grid with distributed generation. Then, in order to obtain better solution results of the objective function, chaotic opposition-based learning (OPL) is introduced to optimize the initial population of the grey wolf algorithm (GWO), so as to obtain better solution results. Finally, the modified IEEE69 node is taken as an example for simulation analysis. The simulation results show that the proposed method can accurately realize the optimal strategy of island partition under local grid fault, ensure the restoration of power supply for important loads, and verify the effectiveness and superiority of the method.