The Study Of PV Array Maximum Power Point Tracking Method

High-efficiency solar energy capture has become one of the hot issues in today’s research. In photovoltaic(PV) system, maximum power point tracking(MPPT) technology is the key technology adjusting the operating voltage of circuit module. To obtain more PV output power. It has attracted more attention,especially in the study of tracking the maximum power point under partial-shading condition of the PV array. Because the output characteristic curve of the PV array is complex, it requires better tracking technology to achieve high efficiency solar energy capture.This thesis analyzes and builds the PV array model, especially under partial-shading condition andmodels and simulats in Matlab / Simulink. Observing the PV array output characteristic curve, such as P-V curve, I-V curves, a number of PV array MPPT methods are proposed, which is applicable to different environments. The experiments show that the proposed methods have high tracking accuracy and tracking speed, compared to other published methods. The study carried out mainly includes the following three aspects:1. PV array output characteristic curve is relatively simple under unobstructed environment. MPPT algorithm is mainly to solve the contradiction between the tracking speed and tracking accuracy. In this study, a self-adaptive step-size MPPT method is presented based on the logarithm calculation. Simulation and experimental results show that the proposed can improve the MPPT response in both speed and accuracy steadily. Compared to other published methods, tracking speed increased 57.1% in simulation and 11.8% in experimental.2. When the PV array under partial-shading condition, there are some problems such as local maximum power points, accurate and fast locking global maximum power point, a method based on narrowing serach range to find the MPP is proposed. Simulation results show that under a variety of complex partial-shading condition, compared to other published methods, the proposed can accurately track the maximum power point.3. Particle swarm optimization(PSO) is applied to solve the PV array MPPT problem. This thesis studies the principle and control processes of PSO, against easily falling into local maximum power points and slow convergence problems. Optimization PSO algorithm is presented based on nonlinear adaptive weighting coefficients. By setting the dispersed initial value of particles and non-linear adaptive inertia weight factor, the maximum power point is tracked. The simulation results show that compared to others, the proposed one has high tracking accuracy and tracking speed and suitable for all-weather conditions.