Maximum Power Tracking Method of Photovoltaic Sequence Based on Nonlinear Particle Swarm Optimization Algorithm  

作　　者：HUANGShouquan 

机构地区：[1]StatePowerInvestmentCorporationShanghaiEnergyTechnologyDevelopmentCo.,Ltd.,Shanghai201100,China

出　　处：《外文科技期刊数据库(文摘版)自然科学》2022年第12期056-062,共7页

摘　　要：Facing the current situation of global energy consumption and increasingly serious environmental pollution, countries have accelerated the construction of new energy systems and put forward the "3060" double-carbon target. Photovoltaic power generation attracts peoples attention, and it has the advantages of renewable and pollution-free, and the installed capacity of photovoltaic is doubled every year. In photovoltaic systems, the common factor that affects the electric quantity is partial occlusion. Different local occlusion affects the I-U output of components, so the traditional MPPT tracking algorithm of series inverter cant reach the maximum output of the array, and is only limited to the local optimal output. Therefore, this paper focuses on the nonlinear characteristics of photovoltaic array output, and optimizes the algorithm based on the conventional particle swarm optimization algorithm. The sim ulation model of photovoltaic sequence used in Hainan Tunchang Xinye Power Station is established by MATLAB/Simulink software. By using the disturbance observation method used by the inverter of the power station and the optimization algorithm particle swarm optimization proposed this time, the maximum power tracking of photovoltaic is analyzed under the conditions of uniform illumination and local shadow, and the peak value of the output characteristic curve of the two algorithms when adjusting the maximum power tracking of photovoltaic sequence is verified.

关 键 词：photovoltaic power generation Particle swarm optimization: Partial occlusion Emulation Simulink 

分 类 号：TM615[电气工程—电力系统及自动化]