Dynamic reconfiguration of distribution network with distributed power supply based on improved artificial fish-swarm algorithm

Abstract

The time-varying characteristics of wind power, photovoltaic power and load are considered comprehensively to solve the problem of distribution network reconfiguration with distributed power generation. The grid connection of distributed power generation will lead to changes in the topology structure and the power flow distribution of the distribution network. In view of the fact that the existing artificial fish swarm algorithm is not enough to deal with it, the artificial fish swarm algorithm is improved and then the distribution network is solved. The hierarchical agglomerative clustering algorithm is used to divide the solar and wind load into time periods. The objective function is network loss and voltage offset. Finally, the improved artificial fish swarm algorithm is used to solve the problem. The defect of the initial AFSA algorithm in the later stage is that it will fall into the local optimum, and the convergence speed and search accuracy are low. In this regard, combined with the differential evolution algorithm, the cross-mutation and other operations are performed on the fish school to increase the diversity of the population, and it can quickly jump out of the local optimum and improve Convergence speed and search accuracy. Experimental results show that the algorithm is feasible and effective for reconstruction.