{"title":"Optimal fuzzy inference for short-term load forecasting","authors":"H. Mori, H. Kobayashi","doi":"10.1109/PICA.1995.515200","DOIUrl":null,"url":null,"abstract":"This paper proposes an optimal fuzzy inference method for short-term load forecasting. The proposed method constructs an optimal structure of the simplified fuzzy inference that minimizes model errors and the number of the membership functions to grasp nonlinear behavior of power system short-term loads. The model is identified by simulated annealing and the steepest descent method. The proposed method is demonstrated in examples.","PeriodicalId":294493,"journal":{"name":"Proceedings of Power Industry Computer Applications Conference","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"198","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of Power Industry Computer Applications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PICA.1995.515200","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 198
Abstract
This paper proposes an optimal fuzzy inference method for short-term load forecasting. The proposed method constructs an optimal structure of the simplified fuzzy inference that minimizes model errors and the number of the membership functions to grasp nonlinear behavior of power system short-term loads. The model is identified by simulated annealing and the steepest descent method. The proposed method is demonstrated in examples.