Research on optimization for the open multi-sources oil-field power net output

Bi Hong-bo, Gao Bing-kun, Zhang Yu-bo
{"title":"Research on optimization for the open multi-sources oil-field power net output","authors":"Bi Hong-bo, Gao Bing-kun, Zhang Yu-bo","doi":"10.1109/CCDC.2009.5191631","DOIUrl":null,"url":null,"abstract":"The oil-field power system and provincial power system belong to the different power system, which purchases the maximal economic benefit respectively. Therefore, under the security restraint, how to cooperate each source output to meet the need of economic operation of the oil-field power system adaptively becomes a very important problem. The mathematical model of oil-field power system output optimization is set up under the market condition, which takes the minimal power cost as the objective function, whose constraints include power supply balance, power station output, line security. At the same time, considering the influence on the actual power price of the net losses generated by the difference of the geographical different sources the modified power price is introduced. Furthermore, the improved genetic algorithm using the chaotic searching method is proposed and applied to the optimization for the oil-field power system. Results show that the improved algorithm can reduce the power costs of the oil-field power system.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Chinese Control and Decision Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2009.5191631","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The oil-field power system and provincial power system belong to the different power system, which purchases the maximal economic benefit respectively. Therefore, under the security restraint, how to cooperate each source output to meet the need of economic operation of the oil-field power system adaptively becomes a very important problem. The mathematical model of oil-field power system output optimization is set up under the market condition, which takes the minimal power cost as the objective function, whose constraints include power supply balance, power station output, line security. At the same time, considering the influence on the actual power price of the net losses generated by the difference of the geographical different sources the modified power price is introduced. Furthermore, the improved genetic algorithm using the chaotic searching method is proposed and applied to the optimization for the oil-field power system. Results show that the improved algorithm can reduce the power costs of the oil-field power system.
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
开放式多源油田电网输出优化研究
油田电力系统与省级电力系统属于不同的电力系统,分别购买最大的经济效益。因此,在安全约束下,如何自适应地协调各源输出以满足油田电力系统经济运行的需要就成为一个非常重要的问题。建立了市场条件下以电力成本最小为目标函数的油田电力系统输出优化数学模型,该模型的约束条件包括供电平衡、电站输出、线路安全。同时,考虑到地理上不同发电源产生的净损失差异对实际电价的影响,引入了修正电价。在此基础上,提出了基于混沌搜索方法的改进遗传算法,并将其应用于油田电力系统的优化。结果表明,改进后的算法可以降低油田电力系统的电力成本。
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
Observer-based H∞ control for discrete-time T-S fuzzy systems Soft sensor for distillation column feeds Design of temperature measure system for variable sensitive temperature range Wavelet neural network based fault diagnosis of asynchronous motor Analysis of the divert ability of atmospheric interceptors controlled by lateral jet thrusters
×
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