{"title":"基于人工神经网络的自主电力系统短期负荷预测数据预处理","authors":"S. Kiartzis, C. Zoumas, A. Bakirtzis, V. Petridis","doi":"10.1109/ICECS.1996.584560","DOIUrl":null,"url":null,"abstract":"This paper presents the development of an Artificial Neural Network (ANN) based short-term load forecasting model for the Dispatching Center of the Greek Public Power Corporation (PPC) in the island of Crete. The model can forecast daily load profiles with a lead time of one to seven days. Experiences gained during the development of the model regarding the selection of the input variables, the ANN structure, and the training data set pre-processing are described in the paper.","PeriodicalId":402369,"journal":{"name":"Proceedings of Third International Conference on Electronics, Circuits, and Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Data pre-processing for short-term load forecasting in an autonomous power system using artificial neural networks\",\"authors\":\"S. Kiartzis, C. Zoumas, A. Bakirtzis, V. Petridis\",\"doi\":\"10.1109/ICECS.1996.584560\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the development of an Artificial Neural Network (ANN) based short-term load forecasting model for the Dispatching Center of the Greek Public Power Corporation (PPC) in the island of Crete. The model can forecast daily load profiles with a lead time of one to seven days. Experiences gained during the development of the model regarding the selection of the input variables, the ANN structure, and the training data set pre-processing are described in the paper.\",\"PeriodicalId\":402369,\"journal\":{\"name\":\"Proceedings of Third International Conference on Electronics, Circuits, and Systems\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of Third International Conference on Electronics, Circuits, and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECS.1996.584560\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of Third International Conference on Electronics, Circuits, and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECS.1996.584560","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data pre-processing for short-term load forecasting in an autonomous power system using artificial neural networks
This paper presents the development of an Artificial Neural Network (ANN) based short-term load forecasting model for the Dispatching Center of the Greek Public Power Corporation (PPC) in the island of Crete. The model can forecast daily load profiles with a lead time of one to seven days. Experiences gained during the development of the model regarding the selection of the input variables, the ANN structure, and the training data set pre-processing are described in the paper.