MPPT Method of Wind Power based on Improved Particle Swarm Optimization

In order to improve the efficiency of wind energy, it is necessary to maximum power point tracking (MPPT). Aiming at shortage of the traditional particle swarm optimization algorithm for parameter sensitivity, easily local convergence, particle swarm optimization (PSO) algorithm with variable neighborhood based on saving preponderant velocities is proposed. Firstly, a compact formula for updating particles is researched, which is considering cognitive discipline of individual on its environment; secondly, a mutation operator with a small probability on the velocities which improve particle quality and a random vector generated for the rest velocities are proposed in order to make full use of good information of particle velocities; finally, the method is applied to maximum power point tracking control of the wind power generation system. The simulation results show that the proposed algorithm can achieve maximum power capture of wind power generation system, improve the dynamic response and efficiency compared with the traditional PSO algorithm