{"title":"基于混合进化智能方法的短期风电预测","authors":"J. Catalão, G. Osório, H. Pousinho","doi":"10.1109/ISAP.2011.6082234","DOIUrl":null,"url":null,"abstract":"This paper presents a hybrid evolutionary intelligent approach, based on a combination of evolutionary particle swarm optimization (EPSO) with an adaptive-network-based fuzzy inference system (ANFIS), for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses challenges due to its intermittency and volatility. Hence, good forecasting tools are important for tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated, reporting the numerical results from a real-world case study.","PeriodicalId":424662,"journal":{"name":"2011 16th International Conference on Intelligent System Applications to Power Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Short-term wind power forecasting using a hybrid evolutionary intelligent approach\",\"authors\":\"J. Catalão, G. Osório, H. Pousinho\",\"doi\":\"10.1109/ISAP.2011.6082234\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a hybrid evolutionary intelligent approach, based on a combination of evolutionary particle swarm optimization (EPSO) with an adaptive-network-based fuzzy inference system (ANFIS), for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses challenges due to its intermittency and volatility. Hence, good forecasting tools are important for tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated, reporting the numerical results from a real-world case study.\",\"PeriodicalId\":424662,\"journal\":{\"name\":\"2011 16th International Conference on Intelligent System Applications to Power Systems\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 16th International Conference on Intelligent System Applications to Power Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISAP.2011.6082234\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 16th International Conference on Intelligent System Applications to Power Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAP.2011.6082234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Short-term wind power forecasting using a hybrid evolutionary intelligent approach
This paper presents a hybrid evolutionary intelligent approach, based on a combination of evolutionary particle swarm optimization (EPSO) with an adaptive-network-based fuzzy inference system (ANFIS), for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses challenges due to its intermittency and volatility. Hence, good forecasting tools are important for tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated, reporting the numerical results from a real-world case study.