Article(id=1321856498993583065, tenantId=1146029695717560320, journalId=1146123222451335185, issueId=1321856374980596274, articleNumber=PA20260928_fRkdRU1P, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1755446400000, receivedDateStr=2025-08-18, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793084748266, onlineDateStr=2026-10-27, pubDate=1770652800000, pubDateStr=2026-02-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793084748266, onlineIssueDateStr=2026-10-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793084748266, creator=admin, updateTime=1793084748266, updator=admin, issue=Issue{id=1321856374980596274, tenantId=1146029695717560320, journalId=1146123222451335185, year='2026', volume='26', issue='3', pageStart='1', pageEnd='341', issueExtLink='null', onlineDate='null', pubDate='1770652800000', pubDateStr='2026-02-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=0, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793084718699, creator='ztmeta', updateTime=1793085648386, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321860274429215699, tenantId=1146029695717560320, journalId=1146123222451335185, issueId=1321856374980596274, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321860274429215700, tenantId=1146029695717560320, journalId=1146123222451335185, issueId=1321856374980596274, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=16, endPage=23, ext={CN=ArticleExt(id=1321856500130239450, articleId=1321856498993583065, tenantId=1146029695717560320, journalId=1146123222451335185, language=CN, title=计及操作风险的智能变电站二次安措优化模型及应用, columnId=null, journalTitle=科技和产业, columnName=科技创新, runingTitle=null, highlight=null, articleAbstract=

智能变电站的二次安措面临隐蔽性强、可视化性差的突出问题,对其改进是实现“削繁降险”的重要途径,但现有方法存在忽视操作风险、操作复杂度评估不全面及求解效率低下等局限。为此,提出一种计及操作风险的智能变电站二次安措优化新模型。该模型引入风险成本来降低操作风险、计入操作复杂度来减少冗余操作,并结合深度神经网络和遗传算法,实现模型高效求解。以220kV线路保护装置为例,验证模型和算法的有效性,为二次安措制定提供了一种新的优化途径。

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