Article(id=1240655021499544519, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655017040991028, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2025.04.012, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1732464000000, receivedDateStr=2024-11-25, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773724807381, onlineDateStr=2026-03-17, pubDate=1766592000000, pubDateStr=2025-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773724807381, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773724807381, creator=13701087609, updateTime=1773724807381, updator=13701087609, issue=Issue{id=1240655017040991028, tenantId=1146029695717560320, journalId=1240618002186551303, year='2025', volume='48', issue='4', pageStart='1', pageEnd='199', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773724806318, creator=13701087609, updateTime=1773725219619, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240656750618145316, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655017040991028, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240656750618145317, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655017040991028, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=103, endPage=112, ext={EN=ArticleExt(id=1240655021818311649, articleId=1240655021499544519, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=Study on the configuration of port microgrids under government hybrid incentives, columnId=1240655021705065434, journalTitle=Navigation of China, columnName=Port and Waterway Engineering, runingTitle=null, highlight=null, articleAbstract=

In the context of carbon emission reduction, this study constructs a bi-level planning model for port microgrid investment and deployment, with the government as the upper-level decision-maker and the port area as the lower-level follower. The model incorporates the interests of the port area, including berthed vessels, and aims to maximize environmental benefits while minimizing the total cost of the port area over the planning period. Using the Column and Constraint Generation (CCG) algorithm, the optimal investment and operation strategy for the port area during the planning horizon is derived. The study analyzes the deployment of the port microgrid system under varying incentive budgets and evaluates the resulting environmental benefits, comparing the effectiveness of different incentive strategies. The results demonstrate that a hybrid incentive strategy can significantly enhance investment motivation in port microgrid systems, thereby effectively fostering innovation in the energy structure of the port region and accelerating the emission reduction process.

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针对碳减排背景下港口微电网的投资部署问题，综合考虑包含在泊船舶在内的港口区域利益，分别以规划期内港区最大化环境效益和港区最小化总成本为目标，构建了以政府为领导者、港区为跟随者的双层规划模型。设计并采用列和约束生成（CCG）算法进行求解，得到划期内港区的最优投资运营策略。分析不同激励预算下港口微电网系统的部署情况与港区的环境效益，并对不同激励策略进行案例对比，结果表明混合激励策略能显著提升港口微电网系统的投资积极性，并有效促进港区能源结构革新与减排进程。

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