Research on MPPT of photovoltaic array based on improved PSO algorithm
In order to solve the problems of particle maturity,slow convergence speed,and easy to fall into local optimization in the traditional particle swarm optimization (PSO )algorithm in the process of optimizing,an improved PSO algorithm which based on reverse learning of logistic-Tent double chaotic mapping and time varying double constrict factor(TVCF)strategy (LT-TVCFPSO)is proposed,on the basis of traditional PSO algorithm,Logistic-Tent chaotic mapping and TVCF are introduced,which can not only enhance the diversity of the population,avoid particle prematurity,and jump out of local optimization,but also speed up the convergence of particle and improve the global optimizing ability.Finally,simulation is carried out by MATLAB/Simulink.Simulation results show that compared with the traditional MPPT algorithm,the LT-TVCFPSO algorithm can quickly and accurately track to the global maximum power point(GMPP).
global optimizingimproved particle swarm optimization algorithmdouble chaotic mappingtime varying double compression factor(TVCF)global maximum power point(GMPP)