{"title":"基于时间序列的风电功率预测研究","authors":"Yumeng Zhang, Yuying Zhao","doi":"10.1109/AIID51893.2021.9456531","DOIUrl":null,"url":null,"abstract":"Due to the uncontrollable characteristics of wind, such as randomness and volatility, the uncertainty of wind power production will be caused to some extent. In order to minimize the influence of wind farm on the stability and safety of the power grid, the prediction of wind power becomes particularly important. In this paper, considering many factors affecting power generation, the ARIMA models based on unary and multivariate time series are used for modeling and analysis of multiple input sequences and output sequences respectively. After comprehensive comparison and analysis, the optimal prediction method is obtained, which provides a new idea for wind power prediction.","PeriodicalId":412698,"journal":{"name":"2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Research on Wind Power Prediction Based on Time Series\",\"authors\":\"Yumeng Zhang, Yuying Zhao\",\"doi\":\"10.1109/AIID51893.2021.9456531\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the uncontrollable characteristics of wind, such as randomness and volatility, the uncertainty of wind power production will be caused to some extent. In order to minimize the influence of wind farm on the stability and safety of the power grid, the prediction of wind power becomes particularly important. In this paper, considering many factors affecting power generation, the ARIMA models based on unary and multivariate time series are used for modeling and analysis of multiple input sequences and output sequences respectively. After comprehensive comparison and analysis, the optimal prediction method is obtained, which provides a new idea for wind power prediction.\",\"PeriodicalId\":412698,\"journal\":{\"name\":\"2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIID51893.2021.9456531\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIID51893.2021.9456531","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Wind Power Prediction Based on Time Series
Due to the uncontrollable characteristics of wind, such as randomness and volatility, the uncertainty of wind power production will be caused to some extent. In order to minimize the influence of wind farm on the stability and safety of the power grid, the prediction of wind power becomes particularly important. In this paper, considering many factors affecting power generation, the ARIMA models based on unary and multivariate time series are used for modeling and analysis of multiple input sequences and output sequences respectively. After comprehensive comparison and analysis, the optimal prediction method is obtained, which provides a new idea for wind power prediction.