Research On Maximum Power Point Tracking For Photovoltaic System Based On Particle Swarm Optimization Algorithm

Photovoltaic (pv) array’s maximum power point tracking control technology is a key technologyfor the pv generation system. Traditional algrithm will fail when applied to PV array in partiallyshade condition and the exact maximum power point can not be found. As a result, a new controlalgorithm for the PV array in partially shade condition is proposed in purpose of improving theefficiency of pv generation.The paper analyzes the physical characteristics of the pv cells and builts the simulation model ofphotovoltaic cells in Matlab/Simulink environment. Analyzes the theory of the hot spot and proposepossibility solution. Then the principle and model of multi-peak maximum power point areanalysised. Analysis of the existing multi-peak maximum power point tracking method and findthere are some limitations of these methods.The basic principles of the standard particle swarm optimization (PSO) are studied and animproved particle swarm algorithm-fallback particle swarm algorithm is proposed according thelimitation of PSO. Then tests the algorithm and find that the algorithm can get a better results thanstandard PSO.Then the algorithm is applied to the multimodal maximum power point tracking control inpartial shade for its good performance in multimodal function global optimization. Builds thesimulation model of the tracking module，The results show that this method can obtain themaximum power point under the case of partial shade accurately. Then builds the simulation modelof each modules in the control system. The results show that the maximum power point of the PVarray can be tracked quickly and accurately, and the output voltage of the PV array can be stablycontrolled near the voltage of the maximum power point, which prove that the proposed canimprove the output efficiency of the PV array effectively.