{"title":"利用混合模型预测开放电力市场的电价","authors":"V. Kurbatsky, N. Tomin","doi":"10.1109/ENERGYCON.2010.5771706","DOIUrl":null,"url":null,"abstract":"The paper presents the results of experimental studies of forecasting prices in the liberalized electricity market. To increase the accuracy price forecasting proposes the hybrid models based on joint usage of the neural network technologies together with Hilbert-Huang Transform. The application of developed hybrid models for hourly prices forecasting has demonstrated the whole accuracy increase forecast","PeriodicalId":386008,"journal":{"name":"2010 IEEE International Energy Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Forecasting prices in the liberalized electricity market using the hybrid models\",\"authors\":\"V. Kurbatsky, N. Tomin\",\"doi\":\"10.1109/ENERGYCON.2010.5771706\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents the results of experimental studies of forecasting prices in the liberalized electricity market. To increase the accuracy price forecasting proposes the hybrid models based on joint usage of the neural network technologies together with Hilbert-Huang Transform. The application of developed hybrid models for hourly prices forecasting has demonstrated the whole accuracy increase forecast\",\"PeriodicalId\":386008,\"journal\":{\"name\":\"2010 IEEE International Energy Conference\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Energy Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ENERGYCON.2010.5771706\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Energy Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ENERGYCON.2010.5771706","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Forecasting prices in the liberalized electricity market using the hybrid models
The paper presents the results of experimental studies of forecasting prices in the liberalized electricity market. To increase the accuracy price forecasting proposes the hybrid models based on joint usage of the neural network technologies together with Hilbert-Huang Transform. The application of developed hybrid models for hourly prices forecasting has demonstrated the whole accuracy increase forecast