{"title":"Application of PSO Algorithm Based on Recognition in MPPT Control of Photovoltaic Array","authors":"Jiaxiong Zhu, Zhigang Xiao, Cao Jing, Chang Feng","doi":"10.12783/DTEEES/PEEES2020/35485","DOIUrl":null,"url":null,"abstract":"Under the condition of local shadow, the P-U curve of photovoltaic array presents multi peak phenomenon. Traditional MPPT algorithm is easy to fail. PSO algorithm is suitable for the optimization of complex multi extremum system, so it is applied in multi peak global MPPT. In order to solve the problem of low precision and premature in PSO algorithm, this paper proposes a new PSO algorithm based on recognition. Through the introduction of awareness, compared with the set value, the particles with better awareness will directly enter the next better iteration, while the particles with poor awareness will be replaced by their historical optimal location, which continues to maintain the search accuracy and speed in the later stage of particle swarm, so as to improve the accuracy and speed of multi peak global optimization. Through the simulation of MATLAB/Simulink, the results show that under the condition of uniform illumination and variable shadow, the particle swarm optimization algorithm based on recognition can effectively improve the convergence speed and accuracy of system optimization.","PeriodicalId":11369,"journal":{"name":"DEStech Transactions on Environment, Energy and Earth Science","volume":"15 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"DEStech Transactions on Environment, Energy and Earth Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12783/DTEEES/PEEES2020/35485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Under the condition of local shadow, the P-U curve of photovoltaic array presents multi peak phenomenon. Traditional MPPT algorithm is easy to fail. PSO algorithm is suitable for the optimization of complex multi extremum system, so it is applied in multi peak global MPPT. In order to solve the problem of low precision and premature in PSO algorithm, this paper proposes a new PSO algorithm based on recognition. Through the introduction of awareness, compared with the set value, the particles with better awareness will directly enter the next better iteration, while the particles with poor awareness will be replaced by their historical optimal location, which continues to maintain the search accuracy and speed in the later stage of particle swarm, so as to improve the accuracy and speed of multi peak global optimization. Through the simulation of MATLAB/Simulink, the results show that under the condition of uniform illumination and variable shadow, the particle swarm optimization algorithm based on recognition can effectively improve the convergence speed and accuracy of system optimization.