{"title":"预测每日积雪反照率随时间变化的模型","authors":"C. Pike, D. Riley, L. Burnham","doi":"10.1109/PVSC48317.2022.9938897","DOIUrl":null,"url":null,"abstract":"As solar photovoltaic technology is deployed in snowier and more northern locations and bifacial module use continues to increase, ground albedo from snow plays a significant role in the energy output of these systems. Accurately knowing the ground albedo allows for more accurate production models. Here we use multiple years of measured snow and albedo data from 6 locations to develop a snow albedo change model that uses time and temperature as the major inputs.","PeriodicalId":435386,"journal":{"name":"2022 IEEE 49th Photovoltaics Specialists Conference (PVSC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Model to Predict Daily Snow Albedo Change Over Time\",\"authors\":\"C. Pike, D. Riley, L. Burnham\",\"doi\":\"10.1109/PVSC48317.2022.9938897\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As solar photovoltaic technology is deployed in snowier and more northern locations and bifacial module use continues to increase, ground albedo from snow plays a significant role in the energy output of these systems. Accurately knowing the ground albedo allows for more accurate production models. Here we use multiple years of measured snow and albedo data from 6 locations to develop a snow albedo change model that uses time and temperature as the major inputs.\",\"PeriodicalId\":435386,\"journal\":{\"name\":\"2022 IEEE 49th Photovoltaics Specialists Conference (PVSC)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 49th Photovoltaics Specialists Conference (PVSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PVSC48317.2022.9938897\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 49th Photovoltaics Specialists Conference (PVSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PVSC48317.2022.9938897","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Model to Predict Daily Snow Albedo Change Over Time
As solar photovoltaic technology is deployed in snowier and more northern locations and bifacial module use continues to increase, ground albedo from snow plays a significant role in the energy output of these systems. Accurately knowing the ground albedo allows for more accurate production models. Here we use multiple years of measured snow and albedo data from 6 locations to develop a snow albedo change model that uses time and temperature as the major inputs.
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