Distribution Network Reconfiguration Method based on Adaptive Multi Population Fruit Fly

Aiming at the nonlinear multi-objective optimization problem of distribution network reconfiguration, the weight of three objective functions, namely network loss, load balance and voltage offset, is determined by the random weight method, which is transformed into a single objective function with the same dimension, the same attribute and the same order of magnitude. The optimal reconfiguration scheme is obtained by using the adaptive multi-population fruit fly optimization algorithm (AMFOA). The node-branch matrix is used for binary coding to avoid the generation of infeasible solutions, and the dynamic step adjustment strategy is introduced to enhance the local search ability of FOA and achieve the effect of balancing global and local search, Cooperative subpopulation strategy and Chebyshev chaotic mapping are used to improve the global search ability and increase the optimization speed. Through the simulation and analysis of a typical IEEE 33-node system with DG, the effectiveness and practicability of the strategy are verified.