B. Vonk, Madeleine Gibescu, E. Veldman, J. Slootweg
{"title":"使用地理和历史天气数据自动生成PV生产概况","authors":"B. Vonk, Madeleine Gibescu, E. Veldman, J. Slootweg","doi":"10.1109/UPEC.2014.6934668","DOIUrl":null,"url":null,"abstract":"This paper introduces on a probabilistic model to automatically generate photovoltaic production profiles for a given geographical region and future scenarios for deployment of renewable energy resources. The model for these profiles uses local properties of buildings, demographic statistics, and historical weather data. Sub-models are calibrated with actual PV data from a smart grid pilot site in the Netherlands and literature based scenarios. It is shown that the model performs adequately and the results are compared with historical data of photovoltaic installations.","PeriodicalId":414838,"journal":{"name":"2014 49th International Universities Power Engineering Conference (UPEC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Automatic PV production profile generation using geographic and historical weather data\",\"authors\":\"B. Vonk, Madeleine Gibescu, E. Veldman, J. Slootweg\",\"doi\":\"10.1109/UPEC.2014.6934668\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces on a probabilistic model to automatically generate photovoltaic production profiles for a given geographical region and future scenarios for deployment of renewable energy resources. The model for these profiles uses local properties of buildings, demographic statistics, and historical weather data. Sub-models are calibrated with actual PV data from a smart grid pilot site in the Netherlands and literature based scenarios. It is shown that the model performs adequately and the results are compared with historical data of photovoltaic installations.\",\"PeriodicalId\":414838,\"journal\":{\"name\":\"2014 49th International Universities Power Engineering Conference (UPEC)\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 49th International Universities Power Engineering Conference (UPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UPEC.2014.6934668\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 49th International Universities Power Engineering Conference (UPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UPEC.2014.6934668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic PV production profile generation using geographic and historical weather data
This paper introduces on a probabilistic model to automatically generate photovoltaic production profiles for a given geographical region and future scenarios for deployment of renewable energy resources. The model for these profiles uses local properties of buildings, demographic statistics, and historical weather data. Sub-models are calibrated with actual PV data from a smart grid pilot site in the Netherlands and literature based scenarios. It is shown that the model performs adequately and the results are compared with historical data of photovoltaic installations.