An approach of DSM techniques for domestic load management using fuzzy logic

R. Pallikonda, Praveen Abbaraju, Vikas Chandra Chinthala, Rashmi Reddy Pabhati Reddy, Karthik Ravi Teja Machiraju
{"title":"An approach of DSM techniques for domestic load management using fuzzy logic","authors":"R. Pallikonda, Praveen Abbaraju, Vikas Chandra Chinthala, Rashmi Reddy Pabhati Reddy, Karthik Ravi Teja Machiraju","doi":"10.1109/FUZZY.2009.5277401","DOIUrl":null,"url":null,"abstract":"Electrical Energy is a vital feature for any developing nation. To meet the growing demand, power generating plants of all types are being installed; even then the gap between the supply and demand is continuously increasing due to the depletion of natural resources. Hence, the way to over come the problem is optimal utilization of available energy sources. In this paper, a methodology is shown to solve to design a model for load management during peak hours in case of domestic loads in both peak hours and off peak hours aiming to reduce the gap between the demand and the supply of electrical energy. Such that consumers and supplier both get beneficial at the same time. The paper also presents the application of fuzzy logic and DSM techniques to the domestic loads, where in the power consumption can be limited during the peak hours there by achieving power conservation. The current method developed is the extension and the part of the Demand Side Management. Simulation results are presented to show effectiveness of the proposed fuzzy logic and Demand Side Management strategy for load management.","PeriodicalId":117895,"journal":{"name":"2009 IEEE International Conference on Fuzzy Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Fuzzy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZY.2009.5277401","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31

Abstract

Electrical Energy is a vital feature for any developing nation. To meet the growing demand, power generating plants of all types are being installed; even then the gap between the supply and demand is continuously increasing due to the depletion of natural resources. Hence, the way to over come the problem is optimal utilization of available energy sources. In this paper, a methodology is shown to solve to design a model for load management during peak hours in case of domestic loads in both peak hours and off peak hours aiming to reduce the gap between the demand and the supply of electrical energy. Such that consumers and supplier both get beneficial at the same time. The paper also presents the application of fuzzy logic and DSM techniques to the domestic loads, where in the power consumption can be limited during the peak hours there by achieving power conservation. The current method developed is the extension and the part of the Demand Side Management. Simulation results are presented to show effectiveness of the proposed fuzzy logic and Demand Side Management strategy for load management.
基于模糊逻辑的需求侧管理技术在国内负荷管理中的应用
电能对任何发展中国家来说都是至关重要的。为了满足日益增长的需求,各种类型的发电厂正在安装;即便如此,由于自然资源的枯竭,供需之间的差距仍在不断扩大。因此,克服这一问题的途径是对现有能源的最佳利用。本文提出了一种方法来解决在高峰时段和非高峰时段家庭负荷的情况下,设计一个高峰时段负荷管理模型,以缩小电力需求和供应之间的差距。使消费者和供应商同时受益。本文还介绍了模糊逻辑和需求侧管理技术在家庭负荷中的应用,在家庭负荷的高峰时段限制用电,实现节电。目前开发的方法是需求侧管理的延伸和部分。仿真结果表明了所提出的模糊逻辑和需求侧管理策略在负荷管理中的有效性。
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 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