{"title":"用谱分析预测短期风速","authors":"H. Akçay, T. Filik","doi":"10.1109/ISSC.2018.8585384","DOIUrl":null,"url":null,"abstract":"In this paper, we apply a wind speed forecasting framework developed earlier by the authors to the two-dimensional wind velocity measurements collected from a meteorological station in the Marmara region of Turkey over a short-term. In the application of the framework, first the measurements are de-trended for the diurnal and the weekly patterns. Other stages of the framework are covariance-factorization via a recently developed subspace method and one–step–ahead and/or multi–step–ahead Kalman filter predictions.","PeriodicalId":174854,"journal":{"name":"2018 29th Irish Signals and Systems Conference (ISSC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Short-Term Wind Speed Forecasting by Spectral Analysis\",\"authors\":\"H. Akçay, T. Filik\",\"doi\":\"10.1109/ISSC.2018.8585384\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we apply a wind speed forecasting framework developed earlier by the authors to the two-dimensional wind velocity measurements collected from a meteorological station in the Marmara region of Turkey over a short-term. In the application of the framework, first the measurements are de-trended for the diurnal and the weekly patterns. Other stages of the framework are covariance-factorization via a recently developed subspace method and one–step–ahead and/or multi–step–ahead Kalman filter predictions.\",\"PeriodicalId\":174854,\"journal\":{\"name\":\"2018 29th Irish Signals and Systems Conference (ISSC)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 29th Irish Signals and Systems Conference (ISSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSC.2018.8585384\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 29th Irish Signals and Systems Conference (ISSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSC.2018.8585384","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Short-Term Wind Speed Forecasting by Spectral Analysis
In this paper, we apply a wind speed forecasting framework developed earlier by the authors to the two-dimensional wind velocity measurements collected from a meteorological station in the Marmara region of Turkey over a short-term. In the application of the framework, first the measurements are de-trended for the diurnal and the weekly patterns. Other stages of the framework are covariance-factorization via a recently developed subspace method and one–step–ahead and/or multi–step–ahead Kalman filter predictions.