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Article(id=1322531290109301283, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1322531228222337541, articleNumber=null, orderNo=null, doi=10.13234/j.issn.2095-2805.2026.3.111, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1688313600000, receivedDateStr=2023-07-03, revisedDate=1693843200000, revisedDateStr=2023-09-05, acceptedDate=1698508800000, acceptedDateStr=2023-10-29, onlineDate=1793245631004, onlineDateStr=2026-10-29, pubDate=1774800000000, pubDateStr=2026-03-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793245631004, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793245631004, creator=13701087609, updateTime=1793245631004, updator=13701087609, issue=Issue{id=1322531228222337541, tenantId=1146029695717560320, journalId=1146031654075715584, year='2026', volume='24', issue='3', pageStart='1', pageEnd='343', issueExtLink='null', onlineDate='null', pubDate='1774800000000', pubDateStr='2026-03-30', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793245616250, creator='13701087609', updateTime=1793245616250, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=111, endPage=118, ext={EN=ArticleExt(id=1322531290495177252, articleId=1322531290109301283, tenantId=1146029695717560320, journalId=1146031654075715584, language=EN, title=Control Strategy for Photovoltaic Hybrid Energy Storage System Based on Model Predictive Control, columnId=1321491614980223555, journalTitle=Journal of Power Supply, columnName=Renewable Energy Generation and Energy Storage, runingTitle=null, highlight=null, articleAbstract=

The energy storage system is an important part of photovoltaic microgrid. However, the traditional battery energy storage system has many problems such as a low power density and a short service life. A supercapacitor hybrid energy storage system based on photovoltaic power generation is established, and its control strategy is proposed, under which the DC-DC converter connected to the energy storage element is controlled through the coordinated operation of model predictive control (MPC) and low-pass filter, and the DC-AC converter connected to the AC side is controlled through a virtual synchronous generator. MPC is a real-time control method, and it can determine the constraints in certain time domain in the future according to the system state at present and optimize the control objectives in the predicted time domain, which has good stability and robustness compared with other control methods. Under changes in the parameters including the intensity of solar radiation, the DC bus voltage can be kept stable, and the dynamic response capability of DC bus voltage can be improved. Finally, the system is simulated in MATLAB/Simulink, and the effectiveness of the proposed method is verified.

, authors=Tao HAI1, Yulin LIU1, Jun WANG2, Jianfeng LU3, authorsList=Tao HAI, Yulin LIU, Jun WANG, Jianfeng LU, authorCompany=null, correspAuthors=Tao HAI, 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=1322531290830721573, articleId=1322531290109301283, tenantId=1146029695717560320, journalId=1146031654075715584, language=CN, title=基于模型预测控制的光伏混合储能系统控制策略, columnId=1321491615269630533, journalTitle=电源学报, columnName=新能源发电与储能, runingTitle=null, highlight=null, articleAbstract=

储能系统是光伏微电网的重要组成部分，传统的蓄电池储能系统存在功率密度低、使用寿命较短等问题，建立了1种以光伏发电为主的超级电容混合储能系统，针对该混合储能系统提出了1种控制策略，该策略通过模型预测控制MPC（model predictive control）与低通滤波器的协同工作，控制与储能元件相连的DC-DC变换器，通过虚拟同步电动机控制与交流侧相连的DC-AC变换器。MPC为1种实时控制方法，可以根据系统的当前状态决定未来一定时域内的约束条件，对预测时域的控制目标进行优化，相较于其他控制方法，具有良好的稳定性和鲁棒性。光照强度等参数变化时，可以使直流母线电压保持稳定，并提高直流母线电压的动态响应能力。最后在MATLAB/Simulink中对系统进行了仿真，验证了该方法的有效性。

, authors=海涛1, 刘昱麟1, 王钧2, 陆剑锋3, authorsList=海涛, 刘昱麟, 王钧, 陆剑锋, authorCompany=null, correspAuthors=海涛, authorNote=

刘昱麟（1998—　），男，硕士研究生。研究方向：光伏发电储能。E-mail：。

王钧（1985—　），男，硕士，高级工程师。研究方向：新能源应用，光伏建筑一体化，光储直柔。E-mail：。

陆剑锋（1978—　），男，硕士，工程师。研究方向：新能源应用。E-mail：。

, correspAuthorsNote=
海涛（1963—　），男，通信作者，本科，教授级高级工程师。研究方向：光伏发电储能，智能检测及电力系统节能。E-mail：。
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刘昱麟（1998—　），男，硕士研究生。研究方向：光伏发电储能。E-mail：。

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刘昱麟（1998—　），男，硕士研究生。研究方向：光伏发电储能。E-mail：。

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王钧（1985—　），男，硕士，高级工程师。研究方向：新能源应用，光伏建筑一体化，光储直柔。E-mail：。

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王钧（1985—　），男，硕士，高级工程师。研究方向：新能源应用，光伏建筑一体化，光储直柔。E-mail：。

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陆剑锋（1978—　），男，硕士，工程师。研究方向：新能源应用。E-mail：。

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基于模型预测控制的光伏混合储能系统控制策略
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海涛 1 , 刘昱麟 1 , 王钧 2 , 陆剑锋 3
电源学报 | 新能源发电与储能 2026,24(3): 111-118
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电源学报 |新能源发电与储能 2026 , 24 (3) : 111 -118
基于模型预测控制的光伏混合储能系统控制策略
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刘昱麟（1998—　），男，硕士研究生。研究方向：光伏发电储能。E-mail：。

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王钧（1985—　），男，硕士，高级工程师。研究方向：新能源应用，光伏建筑一体化，光储直柔。E-mail：。

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陆剑锋（1978—　），男，硕士，工程师。研究方向：新能源应用。E-mail：。

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海涛1 , 刘昱麟1 , 王钧2 , 陆剑锋3
作者信息
  • 1.广西大学电气工程学院，南宁　530004
  • 2.华蓝设计（集团）有限公司，南宁　530004
  • 3.广西中烟工业有限责任公司，南宁　530004
通讯作者:
海涛（1963—　），男，通信作者，本科，教授级高级工程师。研究方向：光伏发电储能，智能检测及电力系统节能。E-mail：。
作者简介:

刘昱麟（1998—　），男，硕士研究生。研究方向：光伏发电储能。E-mail：。

王钧（1985—　），男，硕士，高级工程师。研究方向：新能源应用，光伏建筑一体化，光储直柔。E-mail：。

陆剑锋（1978—　），男，硕士，工程师。研究方向：新能源应用。E-mail：。

Control Strategy for Photovoltaic Hybrid Energy Storage System Based on Model Predictive Control
Tao HAI1 , Yulin LIU1 , Jun WANG2 , Jianfeng LU3
Affiliations
  • 1.College of Electrical Engineering, Guangxi University, Nanning 530004, China
  • 2.Hualan Design Group Co., Ltd., Nanning 530004, China
  • 3.China Tobacco Guangxi Industrial Co., Ltd., Nanning 530004, China
出版时间: 2026-03-30 doi: 10.13234/j.issn.2095-2805.2026.3.111
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摘要
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储能系统是光伏微电网的重要组成部分，传统的蓄电池储能系统存在功率密度低、使用寿命较短等问题，建立了1种以光伏发电为主的超级电容混合储能系统，针对该混合储能系统提出了1种控制策略，该策略通过模型预测控制MPC（model predictive control）与低通滤波器的协同工作，控制与储能元件相连的DC-DC变换器，通过虚拟同步电动机控制与交流侧相连的DC-AC变换器。MPC为1种实时控制方法，可以根据系统的当前状态决定未来一定时域内的约束条件，对预测时域的控制目标进行优化，相较于其他控制方法，具有良好的稳定性和鲁棒性。光照强度等参数变化时，可以使直流母线电压保持稳定，并提高直流母线电压的动态响应能力。最后在MATLAB/Simulink中对系统进行了仿真，验证了该方法的有效性。

微电网  /  混合储能  /  超级电容  /  模型预测控制

The energy storage system is an important part of photovoltaic microgrid. However, the traditional battery energy storage system has many problems such as a low power density and a short service life. A supercapacitor hybrid energy storage system based on photovoltaic power generation is established, and its control strategy is proposed, under which the DC-DC converter connected to the energy storage element is controlled through the coordinated operation of model predictive control (MPC) and low-pass filter, and the DC-AC converter connected to the AC side is controlled through a virtual synchronous generator. MPC is a real-time control method, and it can determine the constraints in certain time domain in the future according to the system state at present and optimize the control objectives in the predicted time domain, which has good stability and robustness compared with other control methods. Under changes in the parameters including the intensity of solar radiation, the DC bus voltage can be kept stable, and the dynamic response capability of DC bus voltage can be improved. Finally, the system is simulated in MATLAB/Simulink, and the effectiveness of the proposed method is verified.

Microgrid  /  hybrid energy storage  /  supercapacitor  /  model predictive control (MPC)
海涛, 刘昱麟, 王钧, 陆剑锋. 基于模型预测控制的光伏混合储能系统控制策略. 电源学报, 2026 , 24 (3) : 111 -118 . DOI: 10.13234/j.issn.2095-2805.2026.3.111
Tao HAI, Yulin LIU, Jun WANG, Jianfeng LU. Control Strategy for Photovoltaic Hybrid Energy Storage System Based on Model Predictive Control[J]. Journal of Power Supply, 2026 , 24 (3) : 111 -118 . DOI: 10.13234/j.issn.2095-2805.2026.3.111
基金
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  • 国家自然科学基金资助项目(51867003)
  • 广西重点研发计划资助项目(桂科AB22035037)
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2026年第24卷第3期
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文章信息
doi: 10.13234/j.issn.2095-2805.2026.3.111
  • 接收时间：2023-07-03
  • 首发时间：2026-10-29
  • 出版时间：2026-03-30
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出版历史
  • 收稿日期：2023-07-03
  • 修回日期：2023-09-05
  • 录用日期：2023-10-29
基金
National Natural Science Foundation of China(51867003)
国家自然科学基金资助项目(51867003)
Guangxi Key R&D Program(桂科AB22035037)
广西重点研发计划资助项目(桂科AB22035037)
作者信息
    1.广西大学电气工程学院，南宁　530004
    2.华蓝设计（集团）有限公司，南宁　530004
    3.广西中烟工业有限责任公司，南宁　530004

通讯作者:

海涛（1963—　），男，通信作者，本科，教授级高级工程师。研究方向：光伏发电储能，智能检测及电力系统节能。E-mail：。
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https://castjournals.cast.org.cn/joweb/dyxb/CN/10.13234/j.issn.2095-2805.2026.3.111
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