Study on two-stage optimal scheduling of DC distribution networks considering flexible load response

IF 1.5 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Lei Chen, Man Yang, Yuqi Jiang, Shencong Zheng, Yifei Li, Xiaoyan You, Hongkun Chen
{"title":"Study on two-stage optimal scheduling of DC distribution networks considering flexible load response","authors":"Lei Chen,&nbsp;Man Yang,&nbsp;Yuqi Jiang,&nbsp;Shencong Zheng,&nbsp;Yifei Li,&nbsp;Xiaoyan You,&nbsp;Hongkun Chen","doi":"10.1049/elp2.12515","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <p>Due to the aim of developing sustainable energy systems, promoting the large-scale accommodation of distributed renewable energy sources (DRESs) and flexible loads in DC distribution networks (DCDNs) is significant. The uncertainty of DRESs and the insufficient use of flexible loads pose a considerable challenge to the economical and safe operation of DCDNs. To address the challenge, this paper puts forward a two-stage optimal scheduling model for the DCDNs considering flexible load response. The proposed model realises joint economic optimisation and reactive power optimisation, which is solved by the hybrid NSGAII-MOPSO algorithm and the CPLEX. The performance of the proposed model in the modified Institute of Electrical and Electronics Engineers 33-node system with the DCDNs is validated under different scenarios. The hybrid NSGAII-MOPSO performs better in obtaining the Pareto front than the NSGA-II and MOPSO individually. Compared to the traditional scheduling model, the proposed model can realise the power coordination of the flexible loads and energy storage systems to reduce the negative impact of uncertainty of DRESs while decreasing operating costs and carbon emissions by 3.94% and 36.4%. In addition, the proposed model can alleviate the network losses and ensure the node voltage for the DCDNs. Hence, the efficiency of the proposed model has been confirmed.</p>\n </section>\n </div>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 11","pages":"1690-1701"},"PeriodicalIF":1.5000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12515","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iet Electric Power Applications","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/elp2.12515","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

Due to the aim of developing sustainable energy systems, promoting the large-scale accommodation of distributed renewable energy sources (DRESs) and flexible loads in DC distribution networks (DCDNs) is significant. The uncertainty of DRESs and the insufficient use of flexible loads pose a considerable challenge to the economical and safe operation of DCDNs. To address the challenge, this paper puts forward a two-stage optimal scheduling model for the DCDNs considering flexible load response. The proposed model realises joint economic optimisation and reactive power optimisation, which is solved by the hybrid NSGAII-MOPSO algorithm and the CPLEX. The performance of the proposed model in the modified Institute of Electrical and Electronics Engineers 33-node system with the DCDNs is validated under different scenarios. The hybrid NSGAII-MOPSO performs better in obtaining the Pareto front than the NSGA-II and MOPSO individually. Compared to the traditional scheduling model, the proposed model can realise the power coordination of the flexible loads and energy storage systems to reduce the negative impact of uncertainty of DRESs while decreasing operating costs and carbon emissions by 3.94% and 36.4%. In addition, the proposed model can alleviate the network losses and ensure the node voltage for the DCDNs. Hence, the efficiency of the proposed model has been confirmed.

Abstract Image

考虑柔性负荷响应的直流配电网两阶段优化调度研究
由于发展可持续能源系统的目标,促进分布式可再生能源(DRESs)和灵活负荷在直流配电网(dcdn)中的大规模容纳具有重要意义。DRESs的不确定性和柔性负载的不充分利用对dcdn的经济安全运行提出了相当大的挑战。为了解决这一问题,本文提出了考虑柔性负载响应的双阶段优化调度模型。该模型实现了联合经济优化和无功优化,并采用混合NSGAII-MOPSO算法和CPLEX进行求解。在改进的美国电气电子工程师学会33节点系统中,采用dcdn验证了该模型在不同场景下的性能。混合nsgai -MOPSO比单独的nsgai - ii和MOPSO具有更好的获得Pareto前的性能。与传统调度模型相比,该模型能够实现柔性负荷与储能系统的电力协调,降低了DRESs不确定性的负面影响,运行成本和碳排放分别降低了3.94%和36.4%。此外,该模型可以减轻网络损耗,保证dcdn的节点电压。因此,该模型的有效性得到了验证。
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
Iet Electric Power Applications
Iet Electric Power Applications 工程技术-工程:电子与电气
CiteScore
4.80
自引率
5.90%
发文量
104
审稿时长
3 months
期刊介绍: IET Electric Power Applications publishes papers of a high technical standard with a suitable balance of practice and theory. The scope covers a wide range of applications and apparatus in the power field. In addition to papers focussing on the design and development of electrical equipment, papers relying on analysis are also sought, provided that the arguments are conveyed succinctly and the conclusions are clear. The scope of the journal includes the following: The design and analysis of motors and generators of all sizes Rotating electrical machines Linear machines Actuators Power transformers Railway traction machines and drives Variable speed drives Machines and drives for electrically powered vehicles Industrial and non-industrial applications and processes Current Special Issue. Call for papers: Progress in Electric Machines, Power Converters and their Control for Wave Energy Generation - https://digital-library.theiet.org/files/IET_EPA_CFP_PEMPCCWEG.pdf
×
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