{"title":"基于遗传算法优化模糊控制器的太阳能光伏系统MPPT技术建模与仿真","authors":"Afshan Ilyas, M. Ayyub, M. R. Khan","doi":"10.1504/ijetp.2020.10026638","DOIUrl":null,"url":null,"abstract":"This paper focuses on the intelligent techniques used for tracking the maximum power point of the solar photovoltaic (SPV) system for varying environmental conditions. The most widely used perturb and observe (P&O) maximum power point tracking (MPPT) technique is discussed briefly for the comparison with the intelligent techniques. The paper proposes control technique for the SPV system by using fuzzy logic controller (FLC)-based MPPT algorithm and the optimisation of its various parameters by genetic algorithm (GA). The performance of the FLC optimised with GA is compared with the P&O and the fuzzy-based MPPT technique. MATLAB/simulink software is used to design the different stages of the MPPT controllers. Simulation results reported that GA optimised FLC perform much better than the P&O and fuzzy logic-based MPPT controllers.","PeriodicalId":35754,"journal":{"name":"International Journal of Energy Technology and Policy","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Modelling and simulation of MPPT techniques for solar photovoltaic system using genetic algorithm optimised fuzzy logic controller\",\"authors\":\"Afshan Ilyas, M. Ayyub, M. R. Khan\",\"doi\":\"10.1504/ijetp.2020.10026638\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper focuses on the intelligent techniques used for tracking the maximum power point of the solar photovoltaic (SPV) system for varying environmental conditions. The most widely used perturb and observe (P&O) maximum power point tracking (MPPT) technique is discussed briefly for the comparison with the intelligent techniques. The paper proposes control technique for the SPV system by using fuzzy logic controller (FLC)-based MPPT algorithm and the optimisation of its various parameters by genetic algorithm (GA). The performance of the FLC optimised with GA is compared with the P&O and the fuzzy-based MPPT technique. MATLAB/simulink software is used to design the different stages of the MPPT controllers. Simulation results reported that GA optimised FLC perform much better than the P&O and fuzzy logic-based MPPT controllers.\",\"PeriodicalId\":35754,\"journal\":{\"name\":\"International Journal of Energy Technology and Policy\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Energy Technology and Policy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijetp.2020.10026638\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Energy Technology and Policy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijetp.2020.10026638","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Social Sciences","Score":null,"Total":0}
Modelling and simulation of MPPT techniques for solar photovoltaic system using genetic algorithm optimised fuzzy logic controller
This paper focuses on the intelligent techniques used for tracking the maximum power point of the solar photovoltaic (SPV) system for varying environmental conditions. The most widely used perturb and observe (P&O) maximum power point tracking (MPPT) technique is discussed briefly for the comparison with the intelligent techniques. The paper proposes control technique for the SPV system by using fuzzy logic controller (FLC)-based MPPT algorithm and the optimisation of its various parameters by genetic algorithm (GA). The performance of the FLC optimised with GA is compared with the P&O and the fuzzy-based MPPT technique. MATLAB/simulink software is used to design the different stages of the MPPT controllers. Simulation results reported that GA optimised FLC perform much better than the P&O and fuzzy logic-based MPPT controllers.