{"title":"Optimum Parameters Extraction of Flexible Photovoltaic Cell Using Earthworm Optimization Algorithm","authors":"Fatima Wardi, Mohamed Louzazni, Mohamed Hanine","doi":"10.1109/ICETSIS61505.2024.10459691","DOIUrl":null,"url":null,"abstract":"The research presents an original approach to estimate and extract the electrical intrinsic characteristics of flexible hydrogenated amorphous silicon (a-Si:H) solar cells using Earthworm Optimization Algorithm (EOA) The EOA metaheuristic algorithm has gained popularity for optimizing non-linear and complicated systems in various fields. Additionally, the current-voltage curve is used to calculate the offered restricted objective function. In addition, the obtained results using EOA are compared with two algorithms named; quasi-Newton technique (Q-N) and self-organizing migration algorithm (SOMA). Finally, to validate the performance of the used algorithm statistical evaluations are calculated to determine the correctness of the calculated parameters. The compared results show that the theoretical results exhibit great agreement with experimental data, demonstrating higher accuracy when compared to Q-N and SOMA.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETSIS61505.2024.10459691","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The research presents an original approach to estimate and extract the electrical intrinsic characteristics of flexible hydrogenated amorphous silicon (a-Si:H) solar cells using Earthworm Optimization Algorithm (EOA) The EOA metaheuristic algorithm has gained popularity for optimizing non-linear and complicated systems in various fields. Additionally, the current-voltage curve is used to calculate the offered restricted objective function. In addition, the obtained results using EOA are compared with two algorithms named; quasi-Newton technique (Q-N) and self-organizing migration algorithm (SOMA). Finally, to validate the performance of the used algorithm statistical evaluations are calculated to determine the correctness of the calculated parameters. The compared results show that the theoretical results exhibit great agreement with experimental data, demonstrating higher accuracy when compared to Q-N and SOMA.