Article(id=1223193057433076509, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223193053830169317, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2023.20220392, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1646236800000, receivedDateStr=2022-03-03, revisedDate=1649088000000, revisedDateStr=2022-04-05, acceptedDate=null, acceptedDateStr=null, onlineDate=1769561550720, onlineDateStr=2026-01-28, pubDate=1674576000000, pubDateStr=2023-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769561550720, onlineIssueDateStr=2026-01-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769561550720, creator=13701087609, updateTime=1769561550720, updator=13701087609, issue=Issue{id=1223193053830169317, tenantId=1146029695717560320, journalId=1205116964453384197, year='2023', volume='41', issue='1', pageStart='1', pageEnd='220', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769561549861, creator=13701087609, updateTime=1769567790701, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1223219229885857794, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223193053830169317, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1223219229885857795, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223193053830169317, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=212, endPage=216, ext={EN=ArticleExt(id=1223193057709900593, articleId=1223193057433076509, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=Topology Optimization of Large-scale Offshore Wind Power Collection System Based on Improved Partheno Genetic Algorithm, columnId=1222940986393744094, journalTitle=Water Resources and Power, columnName=ENERGY, runingTitle=null, highlight=null, articleAbstract=

Aiming at the topology optimization of large-scale offshore wind power collection system, an improved partheno genetic algorithm was proposed. The calculation model of the present value of the life cycle cost of the power collection system was established. Taking the minimum of the sum of present value as the goal, the population generation mode meeting the current carrying capacity constraints of the submarine cable and the elimination coefficient related to the number of crossing points were designed to avoid the submarine cable crossing. The topology of the power collection system with 35 kV and 66 kV voltage levels was optimized and compared. The example results show that the total cost of the improved partheno genetic algorithm can be reduced by 14.2% compared with the traditional algorithm; Compared with 35 kV, 66 kV voltage level has better comprehensive benefits, which can provide reference for the planning and design of large-scale offshore wind farm power collection system.

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针对大规模海上风电集电系统拓扑结构优化问题，提出一种改进单亲遗传算法，建立了集电系统全寿命周期成本现值计算模型，并以现值和最小为目标，通过设计满足海缆载流量约束的种群生成方式和与交叉点个数相关的淘汰系数来避免海缆交叉，优化对比了35、66 kV电压等级的集电系统拓扑结构。算例结果表明，提出的改进单亲遗传算法与传统算法相比总成本可减少14.2%，具有较好的寻优能力；与35 kV相比，集电系统采用66 kV电压等级综合效益更好，可为大规模海上风电场集电系统规划设计提供参考。

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苑玉宽（1997-），男，硕士研究生，研究方向为电力系统规划，E-mail：1414824626@qq.com

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苑玉宽（1997-），男，硕士研究生，研究方向为电力系统规划，E-mail：1414824626@qq.com

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