Management of public water supply to reduce energy cost and improve wind power uptake

R. Kernan, X. Liu, S. McLoone, B. Fox
{"title":"Management of public water supply to reduce energy cost and improve wind power uptake","authors":"R. Kernan, X. Liu, S. McLoone, B. Fox","doi":"10.1109/EEEIC.2016.7555810","DOIUrl":null,"url":null,"abstract":"This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.","PeriodicalId":246856,"journal":{"name":"2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEEIC.2016.7555810","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.
管理公共供水,降低能源成本,提高风力发电
本文介绍了一项关于在北爱尔兰的一个清洁水泵站实施基于实时定价(RTP)的需求侧管理(DSM)抽水的研究,旨在最大限度地降低电力成本并最大限度地利用风力发电的电力。遗传算法(GA)用于根据系统约束和电价情景创建抽水计划。这种方法的实施将使供水网络运营商大大节省电力成本,同时也有助于减轻风力发电的可变性。
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:604180095
Book学术官方微信