{"title":"利用α-β-γ滤波器进行低成本、短期电力负荷预测","authors":"I. Stanciu, C. Șorândaru","doi":"10.1109/INES.2011.5954769","DOIUrl":null,"url":null,"abstract":"As the society evolves and the population grows, the demand for electrical energy increases. Search for new energy resources, increase the efficiency of the existing power plants, and cost minimization are actions to be taken. One way to reduce the cost is predicting the need for electricity. This problem is not new. This paper presents a low-cost method for short-term electric load prediction. After studying his stability, the algorithm is implemented in LabVIEW and a week of power data is used to test it and assess its performance.","PeriodicalId":414812,"journal":{"name":"2011 15th IEEE International Conference on Intelligent Engineering Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Low-cost, short-term electric load prediction using the α-β-γfilter\",\"authors\":\"I. Stanciu, C. Șorândaru\",\"doi\":\"10.1109/INES.2011.5954769\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the society evolves and the population grows, the demand for electrical energy increases. Search for new energy resources, increase the efficiency of the existing power plants, and cost minimization are actions to be taken. One way to reduce the cost is predicting the need for electricity. This problem is not new. This paper presents a low-cost method for short-term electric load prediction. After studying his stability, the algorithm is implemented in LabVIEW and a week of power data is used to test it and assess its performance.\",\"PeriodicalId\":414812,\"journal\":{\"name\":\"2011 15th IEEE International Conference on Intelligent Engineering Systems\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 15th IEEE International Conference on Intelligent Engineering Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INES.2011.5954769\",\"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 15th IEEE International Conference on Intelligent Engineering Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INES.2011.5954769","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Low-cost, short-term electric load prediction using the α-β-γfilter
As the society evolves and the population grows, the demand for electrical energy increases. Search for new energy resources, increase the efficiency of the existing power plants, and cost minimization are actions to be taken. One way to reduce the cost is predicting the need for electricity. This problem is not new. This paper presents a low-cost method for short-term electric load prediction. After studying his stability, the algorithm is implemented in LabVIEW and a week of power data is used to test it and assess its performance.