Article(id=1321481996057031172, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1321481963769287353, articleNumber=null, orderNo=null, doi=10.13234/j.issn.2095-2805.2025.3.208, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1733241600000, receivedDateStr=2024-12-04, revisedDate=1744041600000, revisedDateStr=2025-04-08, acceptedDate=1745424000000, acceptedDateStr=2025-04-24, onlineDate=1792995459808, onlineDateStr=2026-10-26, pubDate=1748534400000, pubDateStr=2025-05-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792995459808, onlineIssueDateStr=2026-10-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792995459807, creator=13701087609, updateTime=1792995459807, updator=13701087609, issue=Issue{id=1321481963769287353, tenantId=1146029695717560320, journalId=1146031654075715584, year='2025', volume='23', issue='3', pageStart='1', pageEnd='372', issueExtLink='null', onlineDate='null', pubDate='1748534400000', pubDateStr='2025-05-30', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792995452109, creator='13701087609', updateTime=1792995578032, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321482491983147168, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1321481963769287353, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321482491983147169, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1321481963769287353, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=208, endPage=219, ext={EN=ArticleExt(id=1321481996317078021, articleId=1321481996057031172, tenantId=1146029695717560320, journalId=1146031654075715584, language=EN, title=Optimal Configuration Method for Energy Storage Taking into Account Lifetime Losses and Demand Response, columnId=1321481964440375995, journalTitle=Journal of Power Supply, columnName=Special Issue on Analysis and Control of Power Quality in New Power Systems, runingTitle=null, highlight=null, articleAbstract=
Aimed at the issue of self-healing and coregulation of distributed energy storage in multi-energy distribution networks under fault, three key aspects are studied, i.e., improving the state estimation accuracy of energy storage batteries, fully utilizing the potential of demand-side load response, and reducing the lifetime losses of energy storage and the system’s operation costs. On this basis, an optimal configuration method for energy storage taking into account lifetime losses and demand response is proposed, which can reduce the lifetime losses of energy storage and the system’s operation costs while realizing the adaptive regulation of states of the energy storage system. First, a recalibration step is added to improve the extended Kalman filter algorithm, and the estimator is allowed to bypass ineffective updates in the meantime, so as to ensure a precise state estimation of energy storage batteries. Second, a demand response model based on price elasticity and behavioral correlation is constructed to optimize the load curves through a dual-effect of price signals and incentive fees. Finally, a mixed-integer linear programming model for energy storage configuration is developed to incorporate the costs of battery lifetime losses, and a demand response model is used to adjust load while integrating the incentive fees into the daily operation cost. Based on the real-time, dynamic and high-precision estimation results, the approach adaptively refines parameters such as the battery lifetime losses and the depth of discharge, as well as the lower and upper bounds of state-of-charge constraints. The analysis results of a case study demonstrate that compared with other models, the proposed model can significantly reduce the lifetime losses of energy storage and the system’s daily operation costs.
, authors=Longjie LI, Meng’en LI, Yong LU, Xianfeng XU, Xinhe BAI, Wanqi LU, authorsList=Longjie LI, Meng’en LI, Yong LU, Xianfeng XU, Xinhe BAI, Wanqi LU, authorCompany=null, correspAuthors=Yong LU, 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=1321481996828783112, articleId=1321481996057031172, tenantId=1146029695717560320, journalId=1146031654075715584, language=CN, title=计及寿命损耗及需求响应的储能优化配置方法, columnId=1149829646675607555, journalTitle=电源学报, columnName=新型电力系统电能质量分析与控制专辑, runingTitle=null, highlight=null, articleAbstract=
针对多元能源配网故障后面向分布式储能的自愈协同调控问题,围绕提升储能电池状态估算精度、充分释放需求侧负荷响应潜力及降低储能寿命损耗与系统运行成本3个方面展开研究,提出1种计及寿命损耗及需求响应的储能优化配置方法,在实现储能系统状态自适应调控的同时,降低储能的寿命损耗与系统运行成本。首先,增添重新校准步骤改进扩展卡尔曼滤波算法,同时允许估计器在更新无用时退出更新,确保储能电池状态估算的精度。然后,构建基于价格弹性及行为关联的需求响应模型,通过价格信号与激励费用双重作用优化负荷曲线。最后,构建计及电池寿命损耗成本的混合整数线性规划储能配置模型,采用需求响应模型进行负荷调整并将激励费用计入日内运行成本,基于获取的储能电池实时动态高精度估计结果对电池寿命损耗与放电深度参数及SOC约束上、下限进行自适应精准调整。算例分析结果表明所提储能配置模型较其他模型能够有效降低储能寿命损耗与系统日内运行成本。
, authors=李陇杰, 李蒙恩, 卢勇, 徐先峰, 白新禾, 鲁婉琪, authorsList=李陇杰, 李蒙恩, 卢勇, 徐先峰, 白新禾, 鲁婉琪, authorCompany=null, correspAuthors=卢勇, authorNote=
徐先峰(1982— ),男,博士,教授。研究方向:交通能源融合,深度学习算法及应用,智能微电网。E-mail:xxf@chd.edu.cn。
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李陇杰(1987— ),男,博士,讲师。研究方向:高电压技术。E-mail:lilongjie@chd.edu.cn。
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李陇杰(1987— ),男,博士,讲师。研究方向:高电压技术。E-mail:lilongjie@chd.edu.cn。
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李蒙恩(2000— ),男,硕士研究生。研究方向:面向分布式储能的配网自愈协同调控技术。E-mail:2023138041@chd.edu.cn。
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李蒙恩(2000— ),男,硕士研究生。研究方向:面向分布式储能的配网自愈协同调控技术。E-mail:2023138041@chd.edu.cn。
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徐先峰(1982— ),男,博士,教授。研究方向:交通能源融合,深度学习算法及应用,智能微电网。E-mail:xxf@chd.edu.cn。
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徐先峰(1982— ),男,博士,教授。研究方向:交通能源融合,深度学习算法及应用,智能微电网。E-mail:xxf@chd.edu.cn。
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白新禾(2001— ),女,硕士研究生。研究方向:微电网配置。E-mail:1206699629@qq.com。
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白新禾(2001— ),女,硕士研究生。研究方向:微电网配置。E-mail:1206699629@qq.com。
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鲁婉琪(2001— ),女,硕士研究生。研究方向:微电网优化。E-mail:2023238010@chd.edu.cn。
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鲁婉琪(2001— ),女,硕士研究生。研究方向:微电网优化。E-mail:2023238010@chd.edu.cn。
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