{"title":"A study of the reduction of the regional aggregated wind power forecast error by spatial smoothing effects in the Maritimes Canada","authors":"Yu Han, Liuchen Chang","doi":"10.1109/EPEC.2010.5697199","DOIUrl":null,"url":null,"abstract":"This research discusses the accuracy of the prediction of aggregated wind power of planned wind farms distributed in the Maritimes Canada. Especially this study calculates and analyzes the aggregated regional wind power forecast error compared to single sites. Using simulated measured wind power and expected wind power from 5 planned wind farms, this research finds that the reduction of the ensemble wind power forecast error depends on the size of the region. To generate these findings, the spatial correlation function of prediction error is applied to calculate the ensemble wind forecast error based on arbitrary configurations of wind farms and wind generations, as long as the total installed wind capacity is a fixed number for the selected planned wind farms. The validation of the spatial smoothing effects will provide the Maritimes utilities an alternative method to reduce the regional aggregated wind power forecast errors instead of using costly wind prediction system.","PeriodicalId":393869,"journal":{"name":"2010 IEEE Electrical Power & Energy Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Electrical Power & Energy Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPEC.2010.5697199","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
This research discusses the accuracy of the prediction of aggregated wind power of planned wind farms distributed in the Maritimes Canada. Especially this study calculates and analyzes the aggregated regional wind power forecast error compared to single sites. Using simulated measured wind power and expected wind power from 5 planned wind farms, this research finds that the reduction of the ensemble wind power forecast error depends on the size of the region. To generate these findings, the spatial correlation function of prediction error is applied to calculate the ensemble wind forecast error based on arbitrary configurations of wind farms and wind generations, as long as the total installed wind capacity is a fixed number for the selected planned wind farms. The validation of the spatial smoothing effects will provide the Maritimes utilities an alternative method to reduce the regional aggregated wind power forecast errors instead of using costly wind prediction system.