Distribution Network Fault Recovery Strategy Based on BPSOGWO Algorithm
In order to further improve the efficiency and reliability of the active distribution network in the process of fault recovery,we analyzed the fault recovery analysis of the active distribution network with a high proportion of dis-tributed power generation based on the particle swarm hybrid gray wolf algorithm.Firstly,aiming at the problems of long duration of fault recovery of distribution network and large fluctuations in output and load demand of photovoltaics and wind turbines,we established a time-varying and load characteristic model of distributed power generation.Taking the maximum amount of important loads recovered by distributed power generation during the fault period as the objec-tive function,we carried out a preliminary islanding of the distribution network.On the basis of the preliminary island division,considering the three objective functions of restoring the maximum amount of important loads,the minimum network loss and the minimum number of switching operations,and using the BPSOGWO algorithm to solve the prob-lem,we obtained the optimal fault recovery strategy for the island and the main network.Simulation verification is car-ried out by using the IEEE 33-node distribution network model,and the results show that the time-varying and load characteristic models of distributed power generation are better,and the active distribution network fault recovery strate-gy based on BPSOGWO algorithm can reliably restore power supply.
distributed generationisolated island partitioningfault recoveryparticle swarm algorithmgrey wolf optimization
万方数据
维普
