A meta-heuristic, moth inspired algorithm for combined economic and environmental power dispatch

Q3 Business, Management and Accounting International Journal of Enterprise Network Management Pub Date : 2018-06-01 DOI:10.1504/IJENM.2018.10013282
N. Mustafa, H. Vennila
{"title":"A meta-heuristic, moth inspired algorithm for combined economic and environmental power dispatch","authors":"N. Mustafa, H. Vennila","doi":"10.1504/IJENM.2018.10013282","DOIUrl":null,"url":null,"abstract":"The problem of deciding the contribution of each generator in a power system is complex. Where some generators are more cost effective, others have cleaner operation. Right choice of generators could save thousands of dollars in operating cost or prevent release of several tons of noxious fumes like NO2 and SO2 annually. Rising complexity of modern power systems and special efficiency improvement methods like valve point loading, demand newer means to find this vital balance between cost and emission. This paper aims to find a solution to this problem by the use of an algorithm inspired by the flight pattern of moths. Like a moth drawn to a flame, this algorithm seeks to minimise both cost as well as emission. The standard IEEE 30 bus test system is considered as the control case and the results obtained are compared with other such algorithms to demonstrate the effectiveness of MFO.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":"9 1","pages":"47"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Enterprise Network Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJENM.2018.10013282","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
引用次数: 1

Abstract

The problem of deciding the contribution of each generator in a power system is complex. Where some generators are more cost effective, others have cleaner operation. Right choice of generators could save thousands of dollars in operating cost or prevent release of several tons of noxious fumes like NO2 and SO2 annually. Rising complexity of modern power systems and special efficiency improvement methods like valve point loading, demand newer means to find this vital balance between cost and emission. This paper aims to find a solution to this problem by the use of an algorithm inspired by the flight pattern of moths. Like a moth drawn to a flame, this algorithm seeks to minimise both cost as well as emission. The standard IEEE 30 bus test system is considered as the control case and the results obtained are compared with other such algorithms to demonstrate the effectiveness of MFO.
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
经济与环境电力联合调度的元启发式、飞蛾启发算法
确定电力系统中每台发电机的贡献是一个复杂的问题。有些发电机更具成本效益,有些则运行更清洁。选择正确的发电机可以节省数千美元的运营成本,或每年防止释放数吨有毒烟雾,如二氧化氮和二氧化硫。现代电力系统的复杂性和特殊的效率提高方法,如阀点加载,需要新的方法来找到成本和排放之间的重要平衡。本文旨在利用一种受飞蛾飞行模式启发的算法来解决这一问题。就像飞蛾扑火一样,这个算法寻求最小化成本和排放量。以标准的ieee30总线测试系统为控制例,并将所得结果与其他同类算法进行了比较,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
International Journal of Enterprise Network Management
International Journal of Enterprise Network Management Business, Management and Accounting-Management of Technology and Innovation
CiteScore
0.90
自引率
0.00%
发文量
28
期刊最新文献
Multi-tier firm-level analysis of global auto supply chain: centrality and financial performance Development of coating material for low carbon steels using MCDM Multi-objective optimisation of wear process parameters of 413/fly ash composites using grey relational analysis Fashion market segmentation using Facebook: an empirical approach Development of coating material for low carbon steels using MCDM
×
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