Intelligent Demand Response Scheme for Customer Side Load Management

Q. B. Dam, S. Mohagheghi, J. Stoupis
{"title":"Intelligent Demand Response Scheme for Customer Side Load Management","authors":"Q. B. Dam, S. Mohagheghi, J. Stoupis","doi":"10.1109/ENERGY.2008.4781013","DOIUrl":null,"url":null,"abstract":"Demand response (DR) provides means for utilities to reduce the power consumption and save energy. Plus, it maximizes utilizing the current capacity of the distribution system infrastructure, reducing or eliminating the need for building new lines and expanding the system. A typical DR program requires two parties to cooperate: the utility and the customers. In this paper a novel intelligent demand response module is designed and proposed to be implemented at the customer side. The primary target of this design is large industrial sized customers that often have several manufacturing/production lines consisting of mostly large electric motors. The proposed DR module design is based on the expert systems theory. Different modules are designed that take the market rates as well as the local load management policy of the customer into account in order to make a decision for reducing the load. The validity of the proposed algorithm is tested on the IEEE 34-bus distribution test feeder in the real-time RT-Lab environment.","PeriodicalId":240093,"journal":{"name":"2008 IEEE Energy 2030 Conference","volume":"153 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"71","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE Energy 2030 Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ENERGY.2008.4781013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 71

Abstract

Demand response (DR) provides means for utilities to reduce the power consumption and save energy. Plus, it maximizes utilizing the current capacity of the distribution system infrastructure, reducing or eliminating the need for building new lines and expanding the system. A typical DR program requires two parties to cooperate: the utility and the customers. In this paper a novel intelligent demand response module is designed and proposed to be implemented at the customer side. The primary target of this design is large industrial sized customers that often have several manufacturing/production lines consisting of mostly large electric motors. The proposed DR module design is based on the expert systems theory. Different modules are designed that take the market rates as well as the local load management policy of the customer into account in order to make a decision for reducing the load. The validity of the proposed algorithm is tested on the IEEE 34-bus distribution test feeder in the real-time RT-Lab environment.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
客户端负荷管理的智能需求响应方案
需求响应(DR)为公用事业提供了减少电力消耗和节约能源的手段。此外,它最大限度地利用了配电系统基础设施的现有容量,减少或消除了建设新线路和扩展系统的需要。典型的灾难恢复计划需要双方合作:公用事业公司和客户。本文设计并提出了一种新的智能需求响应模块,并在客户端实现。本设计的主要目标是大型工业规模的客户,通常有几条主要由大型电动机组成的制造/生产线。提出了基于专家系统理论的DR模块设计方法。设计了不同的模块,将市场价格和客户的本地负荷管理政策考虑在内,以便做出减少负荷的决定。在实时RT-Lab环境下的IEEE 34总线分布测试馈线上验证了该算法的有效性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Framework for Evaluation of Energy Policy Proposals Network reliability assessment towards long term planning AC Grid with Embedded VSC-HVDC for Secure and Efficient Power Delivery Control Strategies for Battery/Supercapacitor Hybrid Energy Storage Systems Power Electronics, a Key Technology for Energy Efficiency and Renewables
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1