{"title":"区域综合能源系统短期负荷预测","authors":"Jianyu Wang","doi":"10.14311/nnw.2021.31.023","DOIUrl":null,"url":null,"abstract":"Based on the theoretical analysis of Elman network, the short-term load forecasting model of regional integrated energy system is established. The structure and parameters of the model are determined through repeated off-line training and experiments. The forecasting accuracy is significantly higher than that of traditional BP network, and the prediction error is less than 3%, which can meet the needs of coordination and scheduling of regional integrated energy system.","PeriodicalId":49765,"journal":{"name":"Neural Network World","volume":"1 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Short-term load forecasting of regional integrated energy system\",\"authors\":\"Jianyu Wang\",\"doi\":\"10.14311/nnw.2021.31.023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the theoretical analysis of Elman network, the short-term load forecasting model of regional integrated energy system is established. The structure and parameters of the model are determined through repeated off-line training and experiments. The forecasting accuracy is significantly higher than that of traditional BP network, and the prediction error is less than 3%, which can meet the needs of coordination and scheduling of regional integrated energy system.\",\"PeriodicalId\":49765,\"journal\":{\"name\":\"Neural Network World\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neural Network World\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.14311/nnw.2021.31.023\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Network World","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.14311/nnw.2021.31.023","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Short-term load forecasting of regional integrated energy system
Based on the theoretical analysis of Elman network, the short-term load forecasting model of regional integrated energy system is established. The structure and parameters of the model are determined through repeated off-line training and experiments. The forecasting accuracy is significantly higher than that of traditional BP network, and the prediction error is less than 3%, which can meet the needs of coordination and scheduling of regional integrated energy system.
期刊介绍:
Neural Network World is a bimonthly journal providing the latest developments in the field of informatics with attention mainly devoted to the problems of:
brain science,
theory and applications of neural networks (both artificial and natural),
fuzzy-neural systems,
methods and applications of evolutionary algorithms,
methods of parallel and mass-parallel computing,
problems of soft-computing,
methods of artificial intelligence.