M. Abbott, G. Xing, G. Scardera, D. Payne, K. McIntosh, Ben A. Sudbury, J. Meydbray, T. Fung, Muhammad Umair Khan, Yu Zhang, S. Zou, Xusheng Wang
{"title":"太阳能电池技术年发电量分析","authors":"M. Abbott, G. Xing, G. Scardera, D. Payne, K. McIntosh, Ben A. Sudbury, J. Meydbray, T. Fung, Muhammad Umair Khan, Yu Zhang, S. Zou, Xusheng Wang","doi":"10.1109/PVSC40753.2019.8980523","DOIUrl":null,"url":null,"abstract":"The ultimate value of any photovoltaic technology is the amount of energy it delivers once installed in the field. Gathering this data experimentally can take many years and requires great cost with limited scope to vary the input parameters. Simulations based on detailed lab measurements provide a more cost-effective option to predict the energy yield of a PV technology rapidly. This paper demonstrates the application of highly detailed ray tracing and SPICE modelling to determine the annual energy yield. It compares the simulated performance of different texturing technologies and predicts the losses at a cell, module and system level. Specifically, it studies upright random pyramids, isotexture and two types of MCCE black silicon applied to a Cz bifacial PERC cell. The difference between isotexture and random pyramids was close to 5% at the cell level, however this significantly reduced to less than 2% at a system level indicating that this analysis is critical to properly assess the ultimate value of a technology.","PeriodicalId":6749,"journal":{"name":"2019 IEEE 46th Photovoltaic Specialists Conference (PVSC)","volume":"39 1","pages":"3046-3050"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Annual energy yield analysis of solar cell technology\",\"authors\":\"M. Abbott, G. Xing, G. Scardera, D. Payne, K. McIntosh, Ben A. Sudbury, J. Meydbray, T. Fung, Muhammad Umair Khan, Yu Zhang, S. Zou, Xusheng Wang\",\"doi\":\"10.1109/PVSC40753.2019.8980523\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The ultimate value of any photovoltaic technology is the amount of energy it delivers once installed in the field. Gathering this data experimentally can take many years and requires great cost with limited scope to vary the input parameters. Simulations based on detailed lab measurements provide a more cost-effective option to predict the energy yield of a PV technology rapidly. This paper demonstrates the application of highly detailed ray tracing and SPICE modelling to determine the annual energy yield. It compares the simulated performance of different texturing technologies and predicts the losses at a cell, module and system level. Specifically, it studies upright random pyramids, isotexture and two types of MCCE black silicon applied to a Cz bifacial PERC cell. The difference between isotexture and random pyramids was close to 5% at the cell level, however this significantly reduced to less than 2% at a system level indicating that this analysis is critical to properly assess the ultimate value of a technology.\",\"PeriodicalId\":6749,\"journal\":{\"name\":\"2019 IEEE 46th Photovoltaic Specialists Conference (PVSC)\",\"volume\":\"39 1\",\"pages\":\"3046-3050\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 46th Photovoltaic Specialists Conference (PVSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PVSC40753.2019.8980523\",\"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 IEEE 46th Photovoltaic Specialists Conference (PVSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PVSC40753.2019.8980523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Annual energy yield analysis of solar cell technology
The ultimate value of any photovoltaic technology is the amount of energy it delivers once installed in the field. Gathering this data experimentally can take many years and requires great cost with limited scope to vary the input parameters. Simulations based on detailed lab measurements provide a more cost-effective option to predict the energy yield of a PV technology rapidly. This paper demonstrates the application of highly detailed ray tracing and SPICE modelling to determine the annual energy yield. It compares the simulated performance of different texturing technologies and predicts the losses at a cell, module and system level. Specifically, it studies upright random pyramids, isotexture and two types of MCCE black silicon applied to a Cz bifacial PERC cell. The difference between isotexture and random pyramids was close to 5% at the cell level, however this significantly reduced to less than 2% at a system level indicating that this analysis is critical to properly assess the ultimate value of a technology.