{"title":"COMPARATIVE ANALYSIS OF CONVENTIONAL, ARTIFICIAL INTELLIGENCE AND HYBRID BASED MPPT TECHNIQUE FOR 852.6-WATT PV SYSTEM","authors":"","doi":"10.4018/ijsesd.302463","DOIUrl":null,"url":null,"abstract":"In this article, Matlab & Simulation software is used for analysis and comparison of 8(Eight) different MPPT. Different MPPT techniques that have been considered in this article are PWM-based, Perturb and Observation (P&O), Incremental Conductance (InC), and Modified InC (MIC) that comes under the Conventional Method. In the Artificial Intelligence, Fuzzy Logic Controller (FLC), Artificial Neural Network (ANN) is chosen and in Hybrid method Neuro-Fuzzy Network (NFN) and Adaptive Neural Fuzzy Inference System (ANFIS) has been considered. PV module of 852.2 Watt is designed with the Boost Converter which can boost the voltage up to 185 Volt for all MPPT. A set of data has been taken for FLC, ANN, NFN, and ANFIS. After implementation, the result has been analyzed for standard test conditions and for the different environmental conditions. In this article, both irradiation and the temperature have been varied together for all MPPT rest are kept constant.","PeriodicalId":38556,"journal":{"name":"International Journal of Social Ecology and Sustainable Development","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Social Ecology and Sustainable Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijsesd.302463","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 1
Abstract
In this article, Matlab & Simulation software is used for analysis and comparison of 8(Eight) different MPPT. Different MPPT techniques that have been considered in this article are PWM-based, Perturb and Observation (P&O), Incremental Conductance (InC), and Modified InC (MIC) that comes under the Conventional Method. In the Artificial Intelligence, Fuzzy Logic Controller (FLC), Artificial Neural Network (ANN) is chosen and in Hybrid method Neuro-Fuzzy Network (NFN) and Adaptive Neural Fuzzy Inference System (ANFIS) has been considered. PV module of 852.2 Watt is designed with the Boost Converter which can boost the voltage up to 185 Volt for all MPPT. A set of data has been taken for FLC, ANN, NFN, and ANFIS. After implementation, the result has been analyzed for standard test conditions and for the different environmental conditions. In this article, both irradiation and the temperature have been varied together for all MPPT rest are kept constant.