{"title":"Parameter extraction of photovoltaic cell using differential evolution method","authors":"K. Ishaque, Z. Salam, H. Taheri, Amir Shamsudin","doi":"10.1109/IAPEC.2011.5779867","DOIUrl":null,"url":null,"abstract":"This paper proposes a new parameter extraction method of photovoltaic cell, based on the differential evolution (DE) technique. The proposed method requires very few control parameters and converges rapidly to a solution. Furthermore, it can fit the I–V curve very accurately irrespective of the values of the initial parameters guesses. The performance of DE is evaluated against the well known genetic algorithm (GA) using a synthetic and experimental I-V data set. It is found that the DE method fits the I–V curve better than GA, has a lower fitness function value and faster execution time.","PeriodicalId":386166,"journal":{"name":"2011 IEEE Applied Power Electronics Colloquium (IAPEC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE Applied Power Electronics Colloquium (IAPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAPEC.2011.5779867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 29
Abstract
This paper proposes a new parameter extraction method of photovoltaic cell, based on the differential evolution (DE) technique. The proposed method requires very few control parameters and converges rapidly to a solution. Furthermore, it can fit the I–V curve very accurately irrespective of the values of the initial parameters guesses. The performance of DE is evaluated against the well known genetic algorithm (GA) using a synthetic and experimental I-V data set. It is found that the DE method fits the I–V curve better than GA, has a lower fitness function value and faster execution time.