{"title":"光伏系统神经模糊MPPT控制的实时实现","authors":"A. Mansouri, F. Krim","doi":"10.1109/ICCIS49240.2020.9257706","DOIUrl":null,"url":null,"abstract":"This paper considers comparison of dynamic performance of incremental conductance technique, fuzzy logic and neuro-fuzzy controllers to track maximum power point of photovoltaic systems. To deliver maximum power, buck-boost maximum power point tracking converter is inserted between photovoltaic generator and load for power adaptation. It is shown that neuro-fuzzy control is superior to fuzzy control and classical incremental conductance method in terms of convergence speed, tracking accuracy and stability under different operating conditions. Experimental results confirm superiority of neuro-fuzzy MPPT over conventional methods.","PeriodicalId":425637,"journal":{"name":"2020 2nd International Conference on Computer and Information Sciences (ICCIS)","volume":"1 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real Time Implementation of Neuro-Fuzzy MPPT Control of PV Systems\",\"authors\":\"A. Mansouri, F. Krim\",\"doi\":\"10.1109/ICCIS49240.2020.9257706\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper considers comparison of dynamic performance of incremental conductance technique, fuzzy logic and neuro-fuzzy controllers to track maximum power point of photovoltaic systems. To deliver maximum power, buck-boost maximum power point tracking converter is inserted between photovoltaic generator and load for power adaptation. It is shown that neuro-fuzzy control is superior to fuzzy control and classical incremental conductance method in terms of convergence speed, tracking accuracy and stability under different operating conditions. Experimental results confirm superiority of neuro-fuzzy MPPT over conventional methods.\",\"PeriodicalId\":425637,\"journal\":{\"name\":\"2020 2nd International Conference on Computer and Information Sciences (ICCIS)\",\"volume\":\"1 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 2nd International Conference on Computer and Information Sciences (ICCIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIS49240.2020.9257706\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 2nd International Conference on Computer and Information Sciences (ICCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS49240.2020.9257706","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real Time Implementation of Neuro-Fuzzy MPPT Control of PV Systems
This paper considers comparison of dynamic performance of incremental conductance technique, fuzzy logic and neuro-fuzzy controllers to track maximum power point of photovoltaic systems. To deliver maximum power, buck-boost maximum power point tracking converter is inserted between photovoltaic generator and load for power adaptation. It is shown that neuro-fuzzy control is superior to fuzzy control and classical incremental conductance method in terms of convergence speed, tracking accuracy and stability under different operating conditions. Experimental results confirm superiority of neuro-fuzzy MPPT over conventional methods.
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