Application of ANN and DSM techniques for peak load management a case study

P. Ravi Babu, V.P. Sree Divya, K. Venkatesh, S. F. Kodad, B.V. Sankar Ram
{"title":"Application of ANN and DSM techniques for peak load management a case study","authors":"P. Ravi Babu, V.P. Sree Divya, K. Venkatesh, S. F. Kodad, B.V. Sankar Ram","doi":"10.1109/SIBIRCON.2008.4602568","DOIUrl":null,"url":null,"abstract":"The resources for electrical energy are depleting and hence the gap between the supply and the demand is continuously increasing. Under such circumstances, the option left is optimal utilization of available energy resources. To overcome this problem recently, a concept of demand side management (DSM) has emerged in power system planning and management. The main idea of DSM is to discuss the mutual benefits between supplier and consumer for maximum benefits and minimum inconvenience. The work presented in this paper gives the results of application of neural network and DSM techniques applied to an industrial consumer. The study indicates the improvement in energy efficiency of the system in terms of load factor, in addition the consumer also gets saving or reduction in the energy bill due to lowering of maximum demand (MD).","PeriodicalId":295946,"journal":{"name":"2008 IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIBIRCON.2008.4602568","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18

Abstract

The resources for electrical energy are depleting and hence the gap between the supply and the demand is continuously increasing. Under such circumstances, the option left is optimal utilization of available energy resources. To overcome this problem recently, a concept of demand side management (DSM) has emerged in power system planning and management. The main idea of DSM is to discuss the mutual benefits between supplier and consumer for maximum benefits and minimum inconvenience. The work presented in this paper gives the results of application of neural network and DSM techniques applied to an industrial consumer. The study indicates the improvement in energy efficiency of the system in terms of load factor, in addition the consumer also gets saving or reduction in the energy bill due to lowering of maximum demand (MD).
人工神经网络和需求侧管理技术在高峰负荷管理中的应用案例研究
电能的资源正在枯竭,因此供需之间的差距不断扩大。在这种情况下,剩下的选择是对可用能源的最优利用。为了克服这一问题,近年来在电力系统规划和管理中出现了需求侧管理的概念。DSM的主要思想是讨论供应商和消费者之间的相互利益,以实现最大的利益和最小的不便。本文给出了神经网络和DSM技术在工业用户中的应用结果。研究表明,在负荷系数方面,系统的能源效率得到了提高,此外,由于最大需求(MD)的降低,消费者的能源账单也得到了节省或减少。
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