增强输电能力和降低电力系统损耗的FACTS设备配置

P. Jirapong
{"title":"增强输电能力和降低电力系统损耗的FACTS设备配置","authors":"P. Jirapong","doi":"10.4018/ijeoe.2013040101","DOIUrl":null,"url":null,"abstract":"In this paper, a hybrid evolutionary algorithm (HEA) is proposed to determine the optimal placement of multi-type flexible AC transmission system (FACTS) devices to simultaneously maximize the total transfer capability (TTC) and minimize the system real power loss of power transfers in deregulated power systems. Multi-objective optimal power flow (OPF) with FACTS devices including TTC, power losses, and penalty functions is used to evaluate the feasible maximum TTC value and minimum power loss within real and reactive power generation limits, thermal limits, voltage limits, stability limits, and FACTS devices operation limits. Test results on the modified IEEE 30-bus system indicate that optimally placed OPF with FACTS by the HEA approach could enhance TTC far more than those from evolutionary programming (EP), tabu search (TS), hybrid tabu search and simulated annealing (TS/SA), and improved evolutionary programming (IEP) algorithms, leading to much efficient utilization of the existing transmission systems.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"FACTS Devices Allocation for Power Transfer Capability Enhancement and Power System Losses Reduction\",\"authors\":\"P. Jirapong\",\"doi\":\"10.4018/ijeoe.2013040101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a hybrid evolutionary algorithm (HEA) is proposed to determine the optimal placement of multi-type flexible AC transmission system (FACTS) devices to simultaneously maximize the total transfer capability (TTC) and minimize the system real power loss of power transfers in deregulated power systems. Multi-objective optimal power flow (OPF) with FACTS devices including TTC, power losses, and penalty functions is used to evaluate the feasible maximum TTC value and minimum power loss within real and reactive power generation limits, thermal limits, voltage limits, stability limits, and FACTS devices operation limits. Test results on the modified IEEE 30-bus system indicate that optimally placed OPF with FACTS by the HEA approach could enhance TTC far more than those from evolutionary programming (EP), tabu search (TS), hybrid tabu search and simulated annealing (TS/SA), and improved evolutionary programming (IEP) algorithms, leading to much efficient utilization of the existing transmission systems.\",\"PeriodicalId\":246250,\"journal\":{\"name\":\"Int. J. Energy Optim. Eng.\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Energy Optim. Eng.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/ijeoe.2013040101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Energy Optim. Eng.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijeoe.2013040101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

本文提出了一种混合进化算法(HEA)来确定多类型柔性交流输电系统(FACTS)设备的最优布局,以同时最大化总传输能力(TTC)和最小化系统实际传输功率损失。多目标最优潮流(OPF)采用FACTS器件,包括TTC、功率损耗和惩罚函数,用于在实际和无功发电限值、热限值、电压限值、稳定性限值和FACTS器件运行限值范围内评估可行的TTC最大值和最小功率损耗。在改进的IEEE 30总线系统上的测试结果表明,采用HEA方法优化放置具有事实的OPF,其TTC的提高效果远远超过进化规划(EP)、禁忌搜索(TS)、禁忌搜索和模拟退火混合(TS/SA)以及改进的进化规划(IEP)算法,从而提高了现有传输系统的利用率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FACTS Devices Allocation for Power Transfer Capability Enhancement and Power System Losses Reduction
In this paper, a hybrid evolutionary algorithm (HEA) is proposed to determine the optimal placement of multi-type flexible AC transmission system (FACTS) devices to simultaneously maximize the total transfer capability (TTC) and minimize the system real power loss of power transfers in deregulated power systems. Multi-objective optimal power flow (OPF) with FACTS devices including TTC, power losses, and penalty functions is used to evaluate the feasible maximum TTC value and minimum power loss within real and reactive power generation limits, thermal limits, voltage limits, stability limits, and FACTS devices operation limits. Test results on the modified IEEE 30-bus system indicate that optimally placed OPF with FACTS by the HEA approach could enhance TTC far more than those from evolutionary programming (EP), tabu search (TS), hybrid tabu search and simulated annealing (TS/SA), and improved evolutionary programming (IEP) algorithms, leading to much efficient utilization of the existing transmission systems.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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