Article(id=1309639341144629805, tenantId=1146029695717560320, journalId=1146119893612605453, issueId=1309639316763149213, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1742832000000, receivedDateStr=2025-03-25, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1790171950851, onlineDateStr=2026-09-23, pubDate=1766160000000, pubDateStr=2025-12-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790171950851, onlineIssueDateStr=2026-09-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790171950851, creator=13701087609, updateTime=1790171950851, updator=13701087609, issue=Issue{id=1309639316763149213, tenantId=1146029695717560320, journalId=1146119893612605453, year='2025', volume='43', issue='12', pageStart='1563', pageEnd='1704', issueExtLink='null', onlineDate='null', pubDate='1766160000000', pubDateStr='2025-12-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790171945038, creator='13701087609', updateTime=1790231727008, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1309890060590346990, tenantId=1146029695717560320, journalId=1146119893612605453, issueId=1309639316763149213, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1309890060594541295, tenantId=1146029695717560320, journalId=1146119893612605453, issueId=1309639316763149213, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1680, endPage=1689, ext={EN=ArticleExt(id=1309639341312401966, articleId=1309639341144629805, tenantId=1146029695717560320, journalId=1146119893612605453, language=EN, title=Economic dispatch strategy for distribution networks considering the frequency regulation characteristics of electric vehicle battery swapping stations and the source-load correlation, columnId=null, journalTitle=Renewable Energy Resources, columnName=null, runingTitle=null, highlight=null, articleAbstract=

To address the power fluctuations in the distribution network caused by the integration of distributed new energy, this article proposes an economic dispatch strategy for the distribution network that considers the frequency regulation capability and source load correlation of electric vehicle battery swapping stations (BSS). This strategy aims to minimize the total system cost, coordinate and schedule frequency modulation resources including BSS, and constrain BSS charging and discharging behavior while maintaining power balance. Firstly, a frequency modulation signal prediction model is constructed: a long short-term memory neural network is used to predict new energy and load power, and the Copula function is used to characterize their correlation, deriving the conditional probability distribution of the frequency modulation signal. Secondly, a prediction driven economic dispatch method based on source load correlation is proposed: Wasserstein distance is used to process the predicted data and construct a fuzzy set, combined with distribution robust optimization and opportunity constraints to establish an economic dispatch model considering the cost of secondary frequency modulation; Further transform the opportunity constraint through conditional value at risk (CVaR) approximation, and use Wasserstein duality to transform the model into a linear programming problem for solution. The simulation results show that the proposed strategy is economically superior to traditional methods.

, authors=Xizheng Zhao¹, Nan Yang¹, Jia Li¹, Jingping Wang¹, Huang Huang¹, Weiqi Pan¹, Shengqi Zhang², authorsList=Xizheng Zhao, Nan Yang, Jia Li, Jingping Wang, Huang Huang, Weiqi Pan, Shengqi Zhang, authorCompany=null, correspAuthors=Shengqi Zhang, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1309639341572448815, articleId=1309639341144629805, tenantId=1146029695717560320, journalId=1146119893612605453, language=CN, title=考虑电动汽车换电站调频特性及源-荷相关性的配网经济调度策略, columnId=null, journalTitle=可再生能源, columnName=, runingTitle=null, highlight=null, articleAbstract=

为应对分布式新能源并网导致的配电网功率波动问题，文章提出一种考虑电动汽车换电站（BSS）调频能力与源-荷相关性的配电网经济调度策略。该策略以系统总成本最小为目标，统筹调度包括BSS在内的调频资源，在维持功率平衡的同时约束BSS充放电行为。首先，构建调频信号预测模型，采用长短期记忆神经网络预测新能源与负荷功率，并利用Copula函数刻画其相关性，推导调频信号的条件概率分布；其次，提出基于源-荷相关性预测驱动的经济调度策略，运用Wasserstein距离处理预测数据并构建模糊集，结合分布鲁棒优化与机会约束建立考虑二次调频成本的经济调度模型，进一步通过条件风险价值（CVaR）近似转化机会约束，并利用Wasserstein对偶性将模型转化为线性规划问题求解。仿真结果表明，所提策略在经济性上优于传统方法。

, authors=赵锡正¹, 杨楠¹, 李佳¹, 王静萍¹, 黄璜¹, 潘炜琪¹, 张圣祺², authorsList=赵锡正, 杨楠, 李佳, 王静萍, 黄璜, 潘炜琪, 张圣祺, authorCompany=null, correspAuthors=张圣祺, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=G7Yw4DiBEc4X0/GtNDZA/A==, magXml=+1JTU/U9Wc8QE9ktl2R8jg==, pdfUrl=null, pdf=/CB/UfasunJsp035wBp3Bw==, pdfFileSize=1527969, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=chJk4MinWXvhrd1WGhHoVw==, mapNumber=null, fund=null)}, authors=[Author(id=1309892233822827512, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1309639341144629805, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1309892233919296506, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1309639341144629805, authorId=1309892233822827512, language=EN, stringName=Xizheng Zhao, firstName=Xizheng, middleName=null, lastName=Zhao, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=^1.State Grid Jiangsu Electric Power Co., Ltd. Nanjing Power Supply Branch, Nanjing 210000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1309892233990599675, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1309639341144629805, authorId=1309892233822827512, language=CN, stringName=赵锡正, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=^1．国网江苏省电力有限公司南京供电分公司，江苏 南京　210000, bio={"content":"

赵锡正（1992-），男，硕士，工程师，主要从事电动汽车管理、配电网能效提升方面的研究。

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赵锡正（1992-），男，硕士，工程师，主要从事电动汽车管理、配电网能效提升方面的研究。

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