M. Brabec, E. Pelikán, P. Krč, K. Eben, P. Musílek
{"title":"光伏农场能源生产的统计模型","authors":"M. Brabec, E. Pelikán, P. Krč, K. Eben, P. Musílek","doi":"10.1109/EPEC.2010.5697249","DOIUrl":null,"url":null,"abstract":"This paper introduces several alternative statistical approaches to modeling and prediction of electric energy generated by photovoltaic farms. The statistical models use outputs of a numerical weather prediction model as their inputs. Presented statistical models allow for easy-to-compute predictions, both in temporal sense and for out-of-sample individual farms. Model performance is illustrated on a sample of real photovoltaic farms located in the Czech Republic.","PeriodicalId":393869,"journal":{"name":"2010 IEEE Electrical Power & Energy Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Statistical modeling of energy production by photovoltaic farms\",\"authors\":\"M. Brabec, E. Pelikán, P. Krč, K. Eben, P. Musílek\",\"doi\":\"10.1109/EPEC.2010.5697249\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces several alternative statistical approaches to modeling and prediction of electric energy generated by photovoltaic farms. The statistical models use outputs of a numerical weather prediction model as their inputs. Presented statistical models allow for easy-to-compute predictions, both in temporal sense and for out-of-sample individual farms. Model performance is illustrated on a sample of real photovoltaic farms located in the Czech Republic.\",\"PeriodicalId\":393869,\"journal\":{\"name\":\"2010 IEEE Electrical Power & Energy Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE Electrical Power & Energy Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EPEC.2010.5697249\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Electrical Power & Energy Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPEC.2010.5697249","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical modeling of energy production by photovoltaic farms
This paper introduces several alternative statistical approaches to modeling and prediction of electric energy generated by photovoltaic farms. The statistical models use outputs of a numerical weather prediction model as their inputs. Presented statistical models allow for easy-to-compute predictions, both in temporal sense and for out-of-sample individual farms. Model performance is illustrated on a sample of real photovoltaic farms located in the Czech Republic.