Generator Load Profiles Estimation Using Artificial Intelligence

A. Ugedo, Enrique Lobato
{"title":"Generator Load Profiles Estimation Using Artificial Intelligence","authors":"A. Ugedo, Enrique Lobato","doi":"10.1109/ISAP.2007.4441586","DOIUrl":null,"url":null,"abstract":"The security criteria of a power system require that branch power flows and bus voltages are within their limits, not only in normal operating conditions but also when any credible contingency occurs. In the Spanish electricity market, voltage constraints are solved by the system operator by connecting a set of off-line generators located in the areas where they occur. Thus, for a market participant it is necessary to predict approximately when its generating units are connected in order to prepare the annual budget and/or decide the time and location of new plants. This paper proposes a methodology to forecast if a non-connected unit will be committed by the system operator in order to remove voltage violations. For that purpose different artificial intelligence techniques are combined: neural networks, decision trees and clustering techniques. The performance of the methodology is illustrated with a study case of a real unit operating in the Spanish market.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Intelligent Systems Applications to Power Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAP.2007.4441586","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

The security criteria of a power system require that branch power flows and bus voltages are within their limits, not only in normal operating conditions but also when any credible contingency occurs. In the Spanish electricity market, voltage constraints are solved by the system operator by connecting a set of off-line generators located in the areas where they occur. Thus, for a market participant it is necessary to predict approximately when its generating units are connected in order to prepare the annual budget and/or decide the time and location of new plants. This paper proposes a methodology to forecast if a non-connected unit will be committed by the system operator in order to remove voltage violations. For that purpose different artificial intelligence techniques are combined: neural networks, decision trees and clustering techniques. The performance of the methodology is illustrated with a study case of a real unit operating in the Spanish market.
基于人工智能的发电机负荷分布估计
电力系统的安全标准要求不仅在正常运行条件下,而且在任何可信的突发事件发生时,支路潮流和母线电压都在其限制范围内。在西班牙电力市场,电压限制是由系统运营商通过连接一组位于该地区的脱机发电机来解决的。因此,对于市场参与者来说,为了准备年度预算和/或决定新电厂的时间和地点,有必要大致预测其发电机组何时并网。本文提出了一种方法来预测系统操作员是否会犯非连接单元,以消除电压违例。为此,我们结合了不同的人工智能技术:神经网络、决策树和聚类技术。该方法的性能是用一个实际单位在西班牙市场运作的研究案例说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信