{"title":"风电预测自回归外生模型的验证与分析","authors":"Ta-Chung Wang, Cheng-Hsun Wu","doi":"10.1109/ICSSE.2018.8520207","DOIUrl":null,"url":null,"abstract":"This research is about building an input-output mathematical model for wind turbine that can be used for forecasting and monitoring. The proposed polynomial modeling of the wind turbine consists of monomials of wind speed and autoregressive terms of the produced power. The results indicate that the proposed approach is fast in computation while maintaining the accuracy of forecasting the generated power output. Moreover, the proposed model is robust in the sense that the model generated is statistically consistent in the presence of randomness of wind speed. A statistical method is also proposed so that the generated model can be used for wind turbine health monitoring.","PeriodicalId":431387,"journal":{"name":"2018 International Conference on System Science and Engineering (ICSSE)","volume":"349 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Verification and Analysist About Autoregressive Exogenous Model for Wind Power Forecasting\",\"authors\":\"Ta-Chung Wang, Cheng-Hsun Wu\",\"doi\":\"10.1109/ICSSE.2018.8520207\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research is about building an input-output mathematical model for wind turbine that can be used for forecasting and monitoring. The proposed polynomial modeling of the wind turbine consists of monomials of wind speed and autoregressive terms of the produced power. The results indicate that the proposed approach is fast in computation while maintaining the accuracy of forecasting the generated power output. Moreover, the proposed model is robust in the sense that the model generated is statistically consistent in the presence of randomness of wind speed. A statistical method is also proposed so that the generated model can be used for wind turbine health monitoring.\",\"PeriodicalId\":431387,\"journal\":{\"name\":\"2018 International Conference on System Science and Engineering (ICSSE)\",\"volume\":\"349 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on System Science and Engineering (ICSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSE.2018.8520207\",\"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 International Conference on System Science and Engineering (ICSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSE.2018.8520207","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Verification and Analysist About Autoregressive Exogenous Model for Wind Power Forecasting
This research is about building an input-output mathematical model for wind turbine that can be used for forecasting and monitoring. The proposed polynomial modeling of the wind turbine consists of monomials of wind speed and autoregressive terms of the produced power. The results indicate that the proposed approach is fast in computation while maintaining the accuracy of forecasting the generated power output. Moreover, the proposed model is robust in the sense that the model generated is statistically consistent in the presence of randomness of wind speed. A statistical method is also proposed so that the generated model can be used for wind turbine health monitoring.