Microgrid distribution system dynamic reactive power optimization based on improved particle swarm algorithms
Wenhao Zhu1,2, Qiyi Guo1, Jianyun Lei3
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(12C) 485-488
1 Department of Electrical Engineering, Tongji University, Shanghai, 200092, China;
2 Schneider Shanghai Low Voltage Terminal Apparatus Co., Ltd. Shanghai, 201109, China;
3 College of Computer Science, South-Central University for Nationalities, Wuhan, 430074, China;
Due to the low accuracy and convergence of existing particle swarm algorithm in the micro power dynamic reactive power optimization in distribution system, this paper proposes an improved particle swarm algorithm based on the state of the particle and inertia weight optimization. This algorithm first adjusts the status of the states of the particles. Then using Sigmoid mapping to optimize the search ability of the inertia weight in particle swarms algorithm. Finally, using the optimal learning strategies to improve the convergence of particle swarm optimization algorithm. Through simulation experiments, the proposed improving particle swarm algorithm based on particle state and inertia weight optimization owing better convergence than traditional particle swarm optimization. Only small error was obtained during dynamic reactive power optimization in micro power distribution system.