基于N-1的启发式静态无功补偿器布置多目标优化

D. Ignatiev, V. Popovtsev
{"title":"基于N-1的启发式静态无功补偿器布置多目标优化","authors":"D. Ignatiev, V. Popovtsev","doi":"10.1109/USSEC53120.2021.9655759","DOIUrl":null,"url":null,"abstract":"The problem of the optimal placement of static var compensator is studied in this paper. Since there is a multitude of parameters that are influenced by static var compensator operation, in addition to various goals of static var compensator installation, the multi-objective optimization problem is being solved. The optimization methods in use are the genetic algorithm and the particle swarm, with the full enumeration method being applied for the purpose of obtaining “benchmark” results to compare with. The variable shunt capacitance is used as static var compensator model in N -1 based power flow calculations. N-l contingencies are proven to be taken into account because their integration into algorithms of static var compensator placement optimization radically changes the results, as it was proven by authors in their previous study. The current research has demonstrated the need to carry out detailed analysis, adjustment and improvement of existing optimization algorithms in order to obtain solutions in the most efficient way. Also sets of objective functions should be carefully selected in accordance with the purpose of device installation, its type and power system operation.","PeriodicalId":260032,"journal":{"name":"2021 Ural-Siberian Smart Energy Conference (USSEC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"N-1 Based Multi-Objective Optimization of Static Var Compensator Placement Using Heuristic Methods\",\"authors\":\"D. Ignatiev, V. Popovtsev\",\"doi\":\"10.1109/USSEC53120.2021.9655759\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of the optimal placement of static var compensator is studied in this paper. Since there is a multitude of parameters that are influenced by static var compensator operation, in addition to various goals of static var compensator installation, the multi-objective optimization problem is being solved. The optimization methods in use are the genetic algorithm and the particle swarm, with the full enumeration method being applied for the purpose of obtaining “benchmark” results to compare with. The variable shunt capacitance is used as static var compensator model in N -1 based power flow calculations. N-l contingencies are proven to be taken into account because their integration into algorithms of static var compensator placement optimization radically changes the results, as it was proven by authors in their previous study. The current research has demonstrated the need to carry out detailed analysis, adjustment and improvement of existing optimization algorithms in order to obtain solutions in the most efficient way. Also sets of objective functions should be carefully selected in accordance with the purpose of device installation, its type and power system operation.\",\"PeriodicalId\":260032,\"journal\":{\"name\":\"2021 Ural-Siberian Smart Energy Conference (USSEC)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Ural-Siberian Smart Energy Conference (USSEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/USSEC53120.2021.9655759\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Ural-Siberian Smart Energy Conference (USSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/USSEC53120.2021.9655759","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文研究了静态无功补偿器的优化布置问题。由于受静态无功补偿器运行影响的参数众多,除了静态无功补偿器安装的各种目标外,还需要解决多目标优化问题。所使用的优化方法有遗传算法和粒子群算法,并采用全枚举方法,以获得“基准”结果进行比较。在基于N -1的潮流计算中,采用可变并联电容作为静态无功补偿器模型。正如作者在之前的研究中所证明的那样,N-l偶然性被考虑在内,因为它们被整合到静态无功补偿器放置优化算法中,从根本上改变了结果。目前的研究表明,为了以最有效的方式获得解,需要对现有的优化算法进行详细的分析、调整和改进。同时,应根据设备的安装目的、类型和电力系统的运行情况,认真选择目标功能的设置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
N-1 Based Multi-Objective Optimization of Static Var Compensator Placement Using Heuristic Methods
The problem of the optimal placement of static var compensator is studied in this paper. Since there is a multitude of parameters that are influenced by static var compensator operation, in addition to various goals of static var compensator installation, the multi-objective optimization problem is being solved. The optimization methods in use are the genetic algorithm and the particle swarm, with the full enumeration method being applied for the purpose of obtaining “benchmark” results to compare with. The variable shunt capacitance is used as static var compensator model in N -1 based power flow calculations. N-l contingencies are proven to be taken into account because their integration into algorithms of static var compensator placement optimization radically changes the results, as it was proven by authors in their previous study. The current research has demonstrated the need to carry out detailed analysis, adjustment and improvement of existing optimization algorithms in order to obtain solutions in the most efficient way. Also sets of objective functions should be carefully selected in accordance with the purpose of device installation, its type and power system operation.
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