Research On Maximum Power Point Tracking Technique Of PV Generation System

Ever growing energy demand by mankind and the limited availability of resources remain as a major challenge to the power sector industry.Among the various renewable energy resources,solar energy has gained worldwide recognition because of its plenty availability,zero noise and zero pollution.Due to various factors such as poor conversion efficiency,high installation cost and the characteristics of solar are non-linear in nature imposing constraints on solar power generation.The maximum power point tracking(MPPT)techniques are thus employed to maximize the power output from solar and to enhance the operating efficiency of the photovoltaic system.In order to research the maximum power point tracking control method for solar power generation system,this paper firstly establishes the mathematical model of solar cells and its arrays,and analyzes the output characteristics of the panels;then classifies the commonly used MPPT methods and analyzes the dynamic externalities in detail.The problem of the MPPT method commonly used in the environment is in the tracking process.Finally,a modified Beta algorithm is proposed under uniform irradiance conditions.An improved technique for photovoltaic multi-peak MPPT based on the local-learning partial swarm optimization(LPSO)is proposed under partial shading conditions.In the case of unifonn irradiance,the modified Beta algorithm uses adaptive factors in the transient stage to automatically adjust parameters according to changes in the external environment,reducing the impact of human factors on algorithm optimization.In the steady-state stage,zero oscillation and incoming current change information are proposed to avoid the deviation problem.In the case of partial shaded,an improved technique for PV multi-peak MPPT based on the LPSO algorithm is adapted to accomplish the detection,achieved by calculating the short-circuit current on the I-U curve and intensity of irradiance at the maximum power point current.In this way,the variance between uniform and partial shading conditions can be effectively distinguished.In addition,the accuracy of the proposed technique can be enhanced by adding local learning to the algorithm of particle swarm optimization.The MPPT simulation model of photovoltaic power generation system was built in MATLAB-Simulink software platform.Compared with the different MPPT techniques through simulation,the simulation results show that the proposed methods can quickly track the changes of external environment and reduce the systematic oscillation near the maximum power point.