Study Of Global MPPT For PV Array Based On Adaptive PSO Algorithm

With the deployment of solar power facilities, the environment which photovoltaic arrayworks in has become more complex. The output curve of photovoltaic array will have thecharacteristic of multi-peak, which has affected the efficiency of photovoltaic array. Therefore,research on global maximum power point tracking (MPPT) for photovoltaic array hastheoretical value and practical significance.Firstly, A deep analysis of the mathematical model for photovoltaic array is made, and asimulation model of photovoltaic array is established. The output characteristic of multi-peakhas been given by the model. The simulation that constant voltage tracking (CVT)andincremental conductance(INC) for global MPPT is given to analyse the inefficieny of thetraditional MPPT. There are two reasons: one is that the failure is related on the relativeposition of the global maximum power point before and after the change of the environment;the other one is that the traditional MPPT methods lack the global searching ability.Secondly, as particle swarm optimization (PSO) has global searching ability, it is usedfor global MPPT. But PSO has shortcomings in searching accuracy and stability, the paperuses adaptive particle swarm optimization (APSO) algorithm for global MPPT according thelimitation of PSO. The evolution state factor and concentration factor are introduced intoAPSO algorithm. The algorithm is divided into three sections by the evolution state factor,different parameters is selected in different periods. And parameters are adjusted at real timeby the concentration factor. A contrast test is made on the benchmark functions, and showsthat the algorithm has a better searching accuracy and stability.Finally, PSO and APSO algorithm for global MPPT are simulated by Matlab/simulink.The simulation results show that APSO algorithm for global MPPT has better searchingaccuracy and stability.