A Reconfiguration Method of Distribution Network Considering Time Variations for Load and Renewable Distributed Generation

J. Wen, Xing Qu, Yinhua Huang, Siyu Lin
{"title":"A Reconfiguration Method of Distribution Network Considering Time Variations for Load and Renewable Distributed Generation","authors":"J. Wen, Xing Qu, Yinhua Huang, Siyu Lin","doi":"10.1109/ACPEE53904.2022.9783804","DOIUrl":null,"url":null,"abstract":"Due to the integration of Renewable Distributed Generation (RDG) and the load demand constantly change in an actual distribution network, network reconfiguration considering variations in load and RDG is a key role to enhance the performances of overall system. This paper proposes a reconfiguration method with time-varying characteristic that aims to minimize the total active power loss and maximize the absorption of RDG power by the system simultaneously. Firstly, the load and RDGs models are built through analyzing the time-varying characteristic of the actual load demand and RDG output power. Afterwards, the comprehensive multi-period objective function is designed based on variations in load and RDG. Finally, a hybrid particle swarm optimization is presented to solve the optimal problem of network reconfiguration considering time-varying characteristic. In the method, the topology structure and the absorption of RDG power are defined as the population which are updated by using integer and random quantum evolution principles. The proposed method is tested on an extended 33-bus network considering actual load demand and RDG to show the effectiveness of enhancing the performance of the system.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPEE53904.2022.9783804","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

Due to the integration of Renewable Distributed Generation (RDG) and the load demand constantly change in an actual distribution network, network reconfiguration considering variations in load and RDG is a key role to enhance the performances of overall system. This paper proposes a reconfiguration method with time-varying characteristic that aims to minimize the total active power loss and maximize the absorption of RDG power by the system simultaneously. Firstly, the load and RDGs models are built through analyzing the time-varying characteristic of the actual load demand and RDG output power. Afterwards, the comprehensive multi-period objective function is designed based on variations in load and RDG. Finally, a hybrid particle swarm optimization is presented to solve the optimal problem of network reconfiguration considering time-varying characteristic. In the method, the topology structure and the absorption of RDG power are defined as the population which are updated by using integer and random quantum evolution principles. The proposed method is tested on an extended 33-bus network considering actual load demand and RDG to show the effectiveness of enhancing the performance of the system.
考虑负荷和可再生分布式发电时变的配电网重构方法
由于可再生分布式发电(RDG)的集成和实际配电网中负荷需求的不断变化,考虑负荷和RDG变化的电网重构是提高整个系统性能的关键。本文提出了一种具有时变特性的重构方法,其目标是使系统的总有功损耗最小,同时使系统对RDG的吸收最大化。首先,通过分析实际负荷需求和RDG输出功率的时变特性,建立了负荷和RDG模型;然后,基于负荷和RDG的变化,设计了综合多期目标函数。最后,提出了一种混合粒子群算法来解决考虑时变特性的网络重构优化问题。在该方法中,将拓扑结构和RDG功率的吸收定义为利用整数和随机量子进化原理更新的总体。在考虑实际负载需求和RDG的扩展33总线网络上进行了测试,证明了该方法提高系统性能的有效性。
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 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:481959085
Book学术官方微信