{"title":"Real time load forecast in power system","authors":"H. Daneshi, A. Daneshi","doi":"10.1109/DRPT.2008.4523494","DOIUrl":null,"url":null,"abstract":"This paper presents an overview of different practical techniques to forecast the load for real time applications. The accuracy of load forecast often determines the amount of energy to be procured in the imbalance market. Therefore to reduce exposures to real-time risks and obtain economic, reliable and secure operations of power system, an accurate real-time forecast is required. It can be used by vertically integrated utilities as well as the ISOs in restructured power system. In this paper, we discuss different approaches based on time series and artificial neural network (ANN). The ISO New England market data are used to illustrate and compare the models.","PeriodicalId":240420,"journal":{"name":"2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DRPT.2008.4523494","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 37

Abstract

This paper presents an overview of different practical techniques to forecast the load for real time applications. The accuracy of load forecast often determines the amount of energy to be procured in the imbalance market. Therefore to reduce exposures to real-time risks and obtain economic, reliable and secure operations of power system, an accurate real-time forecast is required. It can be used by vertically integrated utilities as well as the ISOs in restructured power system. In this paper, we discuss different approaches based on time series and artificial neural network (ANN). The ISO New England market data are used to illustrate and compare the models.
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电力系统负荷实时预测
本文概述了实时应用中预测负载的各种实用技术。负荷预测的准确性往往决定了在不平衡市场中需要获取的电量。因此,为了减少实时风险的暴露,实现电力系统的经济、可靠、安全运行,需要准确的实时预测。它既可用于垂直一体化的公用事业,也可用于重组电力系统中的iso。本文讨论了基于时间序列和人工神经网络(ANN)的不同方法。使用ISO新英格兰市场数据来说明和比较模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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