{"title":"基于时间序列分析的短期负荷预测:一个案例研究","authors":"S. Dodamani, Vinay J Shetty, R. Magadum","doi":"10.1109/TAPENERGY.2015.7229635","DOIUrl":null,"url":null,"abstract":"Short term load forecasting plays a vital role in the daily generation, efficient power system planning, unit maintenance, determining unit commitment and secured power system operation. There are number of approaches for short term load forecasting but it is observed that time series approach is most feasible and provides more reasonable accurate forecast. The present paper discuses the Autoregressive (AR) approach of time series analysis for short term load forecast for Tamilnadu (India) load data. The time series Autoregressive gives better forecasting results for 4 to 6 Hours ahead.","PeriodicalId":6552,"journal":{"name":"2015 International Conference on Technological Advancements in Power and Energy (TAP Energy)","volume":"37 1","pages":"299-303"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Short term load forecast based on time series analysis: A case study\",\"authors\":\"S. Dodamani, Vinay J Shetty, R. Magadum\",\"doi\":\"10.1109/TAPENERGY.2015.7229635\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Short term load forecasting plays a vital role in the daily generation, efficient power system planning, unit maintenance, determining unit commitment and secured power system operation. There are number of approaches for short term load forecasting but it is observed that time series approach is most feasible and provides more reasonable accurate forecast. The present paper discuses the Autoregressive (AR) approach of time series analysis for short term load forecast for Tamilnadu (India) load data. The time series Autoregressive gives better forecasting results for 4 to 6 Hours ahead.\",\"PeriodicalId\":6552,\"journal\":{\"name\":\"2015 International Conference on Technological Advancements in Power and Energy (TAP Energy)\",\"volume\":\"37 1\",\"pages\":\"299-303\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Technological Advancements in Power and Energy (TAP Energy)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAPENERGY.2015.7229635\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Technological Advancements in Power and Energy (TAP Energy)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAPENERGY.2015.7229635","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Short term load forecast based on time series analysis: A case study
Short term load forecasting plays a vital role in the daily generation, efficient power system planning, unit maintenance, determining unit commitment and secured power system operation. There are number of approaches for short term load forecasting but it is observed that time series approach is most feasible and provides more reasonable accurate forecast. The present paper discuses the Autoregressive (AR) approach of time series analysis for short term load forecast for Tamilnadu (India) load data. The time series Autoregressive gives better forecasting results for 4 to 6 Hours ahead.