Article(id=1321485713745498881, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1321485607872872740, articleNumber=null, orderNo=null, doi=10.13234/j.issn.2095-2805.2025.5.251, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1660147200000, receivedDateStr=2022-08-11, revisedDate=1663948800000, revisedDateStr=2022-09-24, acceptedDate=1668096000000, acceptedDateStr=2022-11-11, onlineDate=1792996346173, onlineDateStr=2026-10-26, pubDate=1759161600000, pubDateStr=2025-09-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792996346173, onlineIssueDateStr=2026-10-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792996346173, creator=13701087609, updateTime=1792996346173, updator=13701087609, issue=Issue{id=1321485607872872740, tenantId=1146029695717560320, journalId=1146031654075715584, year='2025', volume='23', issue='5', pageStart='1', pageEnd='332', issueExtLink='null', onlineDate='null', pubDate='1759161600000', pubDateStr='2025-09-30', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792996320932, creator='13701087609', updateTime=1792996886850, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321487981563728115, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1321485607872872740, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321487981563728116, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1321485607872872740, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=251, endPage=261, ext={EN=ArticleExt(id=1321485715549049602, articleId=1321485713745498881, tenantId=1146029695717560320, journalId=1146031654075715584, language=EN, title=Optimal Hybrid Energy Storage Capacity Configuration Method for Mitigating Fluctuations of Wind Power, columnId=1152281491788100462, journalTitle=Journal of Power Supply, columnName=Battery and Energy Storage, runingTitle=null, highlight=null, articleAbstract=

Through a comparison of the economic advantages of different power decomposition methods for energy storage system capacity configuration and hybrid energy storage system (HESS) over one single energy storage system, a method based on improved moving average filtering and ensemble empirical mode decomposition (EEMD) is proposed to mitigate wind power fluctuations in view of the optimal capacity configuration of HESS. First, EEMD was used to decompose the HESS reference power which was derived by improved moving average filtering, so as to obtain several single-component signals, i.e., intrinsic mode functions (IMFs). Then, the time-frequency spectrum of each IMF was processed by Hilbert transform to identify the suitable gap frequency, and the HESS reference power was obtained by reconstructing the high- and low-frequency components. Meanwhile, the charge-discharge efficiency of the energy storage system and its state-of-charge were fully taken into account, and the rated power and capacities were configured. Finally, based on the life cycle cost theory, an economic cost calculation model for the energy storage system was established to compare the cost among different configuration schemes, thereby obtaining the optimal one with the highest economic efficiency.

, authors=Yuming CHENG¹, Gaojun MENG², Peng JIA¹, Yao WU², authorsList=Yuming CHENG, Gaojun MENG, Peng JIA, Yao WU, authorCompany=null, correspAuthors=Gaojun MENG, 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=1321485716018811653, articleId=1321485713745498881, tenantId=1146029695717560320, journalId=1146031654075715584, language=CN, title=用于平抑风电功率波动的混合储能容量优化配置方法, columnId=1149830274575463188, journalTitle=电源学报, columnName=电池与储能, runingTitle=null, highlight=null, articleAbstract=

通过比较不同功率分解方法用于储能系统容量配置以及混合储能系统HESS（hybrid energy storage system）相对于单一储能系统的经济优势，针对HESS容量优化配置提出了1种基于改进滑动平均滤波和集合经验模态分解EEMD（ensemble empirical mode decomposition）的平抑风电功率波动的方法。首先利用改进滑动平均滤波获得HESS的参考功率，采用EEMD分解将其分解为多个单分量信号—固有模态函数IMF（intrinsic mode function），并通过希尔伯特变换得到各IMF的时频谱以确定合适的分频频率，将高、低频分量重构得到HESS的参考功率。同时，充分考虑储能系统的充放电效率和荷电状态，配置额定功率和容量。最后，基于全寿命周期成本理论构建储能系统经济成本计算模型，比较不同方案的成本，得到经济最优的配置方案。

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程昱明（1987—　），男，博士，高级工程师。研究方向：新能源与电网规划研究。E-mail：308215343@qq.com。

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程昱明（1987—　），男，博士，高级工程师。研究方向：新能源与电网规划研究。E-mail：308215343@qq.com。

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贾鹏（1982—　），男，博士，副教授。研究方向：先进储能技术。E-mail：510761967@qq.com。

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