Distribution Network Regionalized Fault Location Based on an Improved Manta Ray Foraging Optimization Algorithm

To address the problem that accuracy of traditional intelligent algorithms in distribution network fault location decreases with expansion scale, a regionalized method for networks containing distributed power sources based on improved manta ray foraging optimization (IMRFO) algorithm is proposed. First, global convergence property basic (MRFO) by fusing restart strategy and opposition-based learning strategy. Then, two-port equivalence principle, topological model hierarchical localization constructed. Finally, binary discretization using Sigmoid function to output vector complete network. Simulation experiments are conducted MATLAB IEEE-33 node simulation results show IMRFO combined regionalization complex has better effect dimensionality reduction. Compared model, tolerance greatly its rate increased 1.8% speed 15.537 ms.