Article(id=1223190874155238358, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223190866320278179, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2023.20230327, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1678032000000, receivedDateStr=2023-03-06, revisedDate=1681920000000, revisedDateStr=2023-04-20, acceptedDate=null, acceptedDateStr=null, onlineDate=1769561030185, onlineDateStr=2026-01-28, pubDate=1695571200000, pubDateStr=2023-09-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769561030185, onlineIssueDateStr=2026-01-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769561030185, creator=13701087609, updateTime=1769561030185, updator=13701087609, issue=Issue{id=1223190866320278179, tenantId=1146029695717560320, journalId=1205116964453384197, year='2023', volume='41', issue='9', 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=1769561028318, creator=13701087609, updateTime=1769562015483, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1223195006870082478, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223190866320278179, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1223195006870082479, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223190866320278179, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=180, endPage=184, ext={EN=ArticleExt(id=1223190874608223209, articleId=1223190874155238358, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=Startup Optimization of Hydroelectric Generating Set Based on Improved Grey Wolf Search Coupled Cuckoo Algorithm, columnId=1222925284869922957, journalTitle=Water Resources and Power, columnName=ELECTROMECHANICS AND CONTROL ENGINEERING, runingTitle=null, highlight=null, articleAbstract=

In order to shorten the start-up time of the hydroelectric generating set and improve the stability of the generating set 's start-up process and non-loading, a start-up optimization strategy of hydropower unit based on improved grey wolf search coupling cuckoo algorithm was proposed. This fitness function weighs the two index values of the unit ' s start-up frequency ITAE index and the unit 's start-up time and standardizes them. Two penalty functions of unit frequency overshoot and unit frequency steady-state error are introduced to effectively improve the start-up performance evaluation index of the hydroelectric generating set. An improved grey wolf search coupled cuckoo algorithm (IGWSCSA) based on good point set theory to improve the initial population is proposed to optimize the start-up parameters of the generating set. Based on the simulation experiment of the refined model of the speed control system, the optimal parameters are obtained to shorten the start-up adjustment time of the generating set, and the overshoot is reduced from 0.235 to 0.004, which greatly optimizes the start-up speed and frequency fluctuation of the hydroelectric generating set.

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为缩短水力发电机组开机时间，提高机组开机过程和空载稳定性，提出一种基于改进灰狼搜索耦合杜鹃算法的水力发电机组启动优化策略，建立开机适应度函数，该函数权衡机组开机频率ITAE指标和机组开机时间两个指标数值并将其标幺化，引入机组频率超调量和机组频率稳态误差两个惩罚函数，从而有效改善机组启动性能评价指标，且提出一种佳点集理论改进初始种群的改进灰狼搜索耦合杜鹃算法（IGWSCSA）针对机组启动参数进行精确优化。基于调速系统精细化模型的仿真试验得到最优参数使机组开机调节时间明显缩短，超调量由0.235降低至0.004，极大优化了水力发电机组启动的开机速度和频率波动。

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李佰霖（1987-），男，博士、讲师、硕导，研究方向为水力发电厂运维数字化，电力设备在线监测与故障诊断，E-mail：libailin@ctgu.edu.cn

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李佰霖（1987-），男，博士、讲师、硕导，研究方向为水力发电厂运维数字化，电力设备在线监测与故障诊断，E-mail：libailin@ctgu.edu.cn

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