{"title":"从In[Jsc]-Voc和FF-Voc特性中提取串联电阻","authors":"A. Haas, J. Wilcox, J. Gray, R. J. Schwartz","doi":"10.1109/PVSC.2011.6185998","DOIUrl":null,"url":null,"abstract":"Solar concentrator systems often employ complex optical and electrical components such as lenses, dichroic mirrors, and inverters. Embedding solar cell models into a system analysis tool, such as an optical modeling tool, facilitates system optimization. Polynomial curve-fit based models are useful for this purpose, as they accurately and reliably predict measured cell performance over a wide range of intensity. In this paper, it is shown that the curve-fit model allows for the extraction of an intensity-dependent ideality factor and effective series resistance. A case study is performed on a published GaAs concentrator solar cell. The series resistance extracted from the model is within 10% of the expected value.","PeriodicalId":373149,"journal":{"name":"2011 37th IEEE Photovoltaic Specialists Conference","volume":"136 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Extracting a series resistance from In[Jsc]-Voc and FF-Voc characteristics\",\"authors\":\"A. Haas, J. Wilcox, J. Gray, R. J. Schwartz\",\"doi\":\"10.1109/PVSC.2011.6185998\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Solar concentrator systems often employ complex optical and electrical components such as lenses, dichroic mirrors, and inverters. Embedding solar cell models into a system analysis tool, such as an optical modeling tool, facilitates system optimization. Polynomial curve-fit based models are useful for this purpose, as they accurately and reliably predict measured cell performance over a wide range of intensity. In this paper, it is shown that the curve-fit model allows for the extraction of an intensity-dependent ideality factor and effective series resistance. A case study is performed on a published GaAs concentrator solar cell. The series resistance extracted from the model is within 10% of the expected value.\",\"PeriodicalId\":373149,\"journal\":{\"name\":\"2011 37th IEEE Photovoltaic Specialists Conference\",\"volume\":\"136 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 37th IEEE Photovoltaic Specialists Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PVSC.2011.6185998\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 37th IEEE Photovoltaic Specialists Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PVSC.2011.6185998","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extracting a series resistance from In[Jsc]-Voc and FF-Voc characteristics
Solar concentrator systems often employ complex optical and electrical components such as lenses, dichroic mirrors, and inverters. Embedding solar cell models into a system analysis tool, such as an optical modeling tool, facilitates system optimization. Polynomial curve-fit based models are useful for this purpose, as they accurately and reliably predict measured cell performance over a wide range of intensity. In this paper, it is shown that the curve-fit model allows for the extraction of an intensity-dependent ideality factor and effective series resistance. A case study is performed on a published GaAs concentrator solar cell. The series resistance extracted from the model is within 10% of the expected value.