{"title":"周末短期负荷预测案例研究","authors":"N. A. Salim, T. Rahman, M. F. Jamaludin, M. Musa","doi":"10.1109/SCORED.2009.5443006","DOIUrl":null,"url":null,"abstract":"This paper presents the Short Term Load Forecasting (STLF) to predict the demand in the future. STLF is a method used to predict a day ahead, 24 hours load demand. Two factors were considered in this forecasting: time and also the temperature of the day. The main objective of this project is to analyze the profile or pattern of the forecasted load and also to predict the load demand during weekends. Artificial Neural Network (ANN) in MATLAB software was used in solving the forecasting problem. The percentage of average error was determined by using the Mean Absolute Percentage Error (MAPE).","PeriodicalId":443287,"journal":{"name":"2009 IEEE Student Conference on Research and Development (SCOReD)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Case study of Short Term Load Forecasting for weekends\",\"authors\":\"N. A. Salim, T. Rahman, M. F. Jamaludin, M. Musa\",\"doi\":\"10.1109/SCORED.2009.5443006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the Short Term Load Forecasting (STLF) to predict the demand in the future. STLF is a method used to predict a day ahead, 24 hours load demand. Two factors were considered in this forecasting: time and also the temperature of the day. The main objective of this project is to analyze the profile or pattern of the forecasted load and also to predict the load demand during weekends. Artificial Neural Network (ANN) in MATLAB software was used in solving the forecasting problem. The percentage of average error was determined by using the Mean Absolute Percentage Error (MAPE).\",\"PeriodicalId\":443287,\"journal\":{\"name\":\"2009 IEEE Student Conference on Research and Development (SCOReD)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Student Conference on Research and Development (SCOReD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCORED.2009.5443006\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Student Conference on Research and Development (SCOReD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCORED.2009.5443006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Case study of Short Term Load Forecasting for weekends
This paper presents the Short Term Load Forecasting (STLF) to predict the demand in the future. STLF is a method used to predict a day ahead, 24 hours load demand. Two factors were considered in this forecasting: time and also the temperature of the day. The main objective of this project is to analyze the profile or pattern of the forecasted load and also to predict the load demand during weekends. Artificial Neural Network (ANN) in MATLAB software was used in solving the forecasting problem. The percentage of average error was determined by using the Mean Absolute Percentage Error (MAPE).
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