{"title":"利用迄今最佳ABC算法提取光伏组件参数","authors":"E. Garoudja, W. Filali","doi":"10.1109/ICAEE47123.2019.9015191","DOIUrl":null,"url":null,"abstract":"In the present work, a nature inspired algorithm, which is the best-so-far Artificial Bee Colony algorithm, has been used to make the extraction of the electrical parameters of a Photovoltaic (PV) module. This algorithm emulates the behavior of bees in nature, where they search their food sources, to identify the one diode model (ODM) parameters. The effectiveness of our strategy has been checked by using two types of electrical characteristics (I-V and P-V) obtained from the simulation of LG395N2W PV module at two operating conditions. Finally, a comparative study has been elaborated with other heuristic algorithm, Particle Swarm Optimization (PSO) algorithm. Results show clearly that the best-so-far ABC noticeably outperforms PSO in the parameters accuracy, fitness value and convergence rate.","PeriodicalId":197612,"journal":{"name":"2019 International Conference on Advanced Electrical Engineering (ICAEE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Photovoltaic module parameters extraction using best-so-far ABC algorithm\",\"authors\":\"E. Garoudja, W. Filali\",\"doi\":\"10.1109/ICAEE47123.2019.9015191\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the present work, a nature inspired algorithm, which is the best-so-far Artificial Bee Colony algorithm, has been used to make the extraction of the electrical parameters of a Photovoltaic (PV) module. This algorithm emulates the behavior of bees in nature, where they search their food sources, to identify the one diode model (ODM) parameters. The effectiveness of our strategy has been checked by using two types of electrical characteristics (I-V and P-V) obtained from the simulation of LG395N2W PV module at two operating conditions. Finally, a comparative study has been elaborated with other heuristic algorithm, Particle Swarm Optimization (PSO) algorithm. Results show clearly that the best-so-far ABC noticeably outperforms PSO in the parameters accuracy, fitness value and convergence rate.\",\"PeriodicalId\":197612,\"journal\":{\"name\":\"2019 International Conference on Advanced Electrical Engineering (ICAEE)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Advanced Electrical Engineering (ICAEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAEE47123.2019.9015191\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Advanced Electrical Engineering (ICAEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAEE47123.2019.9015191","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Photovoltaic module parameters extraction using best-so-far ABC algorithm
In the present work, a nature inspired algorithm, which is the best-so-far Artificial Bee Colony algorithm, has been used to make the extraction of the electrical parameters of a Photovoltaic (PV) module. This algorithm emulates the behavior of bees in nature, where they search their food sources, to identify the one diode model (ODM) parameters. The effectiveness of our strategy has been checked by using two types of electrical characteristics (I-V and P-V) obtained from the simulation of LG395N2W PV module at two operating conditions. Finally, a comparative study has been elaborated with other heuristic algorithm, Particle Swarm Optimization (PSO) algorithm. Results show clearly that the best-so-far ABC noticeably outperforms PSO in the parameters accuracy, fitness value and convergence rate.