Article(id=1221459821832884520, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1221459819031085880, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202208219, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1661875200000, receivedDateStr=2022-08-31, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1769148315151, onlineDateStr=2026-01-23, pubDate=1679673600000, pubDateStr=2023-03-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769148315151, onlineIssueDateStr=2026-01-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769148315151, creator=13701087609, updateTime=1769148315151, updator=13701087609, issue=Issue{id=1221459819031085880, tenantId=1146029695717560320, journalId=1210938733613449225, year='2023', volume='52', issue='3', pageStart='1', pageEnd='167', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769148314483, creator=13701087609, updateTime=1769149441207, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1221464544916983885, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1221459819031085880, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1221464544916983886, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1221459819031085880, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=49, endPage=57, ext={EN=ArticleExt(id=1221459822155845939, articleId=1221459821832884520, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Health assessment of wind turbine IGBT based on dynamic regularization and Park vector centrifugal change rate, columnId=1221459819714757434, journalTitle=Thermal Power Generation, columnName=Fault diagnosis and condition monitoring technologies of wind power system, runingTitle=null, highlight=null, articleAbstract=

In view of the high failure rate of the insulated gate bipolar transistor (IGBT) of wind turbine converter and the fact that the failure occurs on a short time scale, a health state assessment method of the IGBT based on dynamic regularization and Park vector centrifugal change rate is proposed. The similarity calculation model is established by using the dynamic regularization algorithm to calculate the minimum regularization distance and waveform similarity of three-phase waveforms to judge the condition of the converter. The centrifugal rate and change rate of Park vector ellipse are used to evaluate the IGBT status and set the evaluation index. Moreover, the practicability is verified by simulation data and operation data, respectively. The results reveal that, these two methods have good practicability, the waveform similarity decreases gradually before the fault occurs, and the change trend of Park vector eccentricity continues to increase, which proves that the two algorithm models can clearly distinguish between normal and abnormal waveforms. Using these two methods can timely feed back of the converter health status, thus to effectively avoid the shutdown or damage of the power electronic system due to the IGBT fault and avoid the property loss caused by equipment fault.

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针对风电机组变流器绝缘栅双极型晶体管（IGBT）模块故障率高且故障发生在较短时间尺度上的情况，提出基于动态规整与Park矢量离心变化率的变流器IGBT健康状态评估方法，利用动态规整算法建立相似度计算模型，计算三相波形的最小规整距离与波形相似度并实现变流器运行状态判断；利用Park矢量椭圆离心率与变化率进行IGBT状态评估并设定评估指标。分别通过仿真及实际运行数据验证。验证结果表明，该方法具有较好的实用性，在故障发生前波形相似度逐渐降低，Park矢量离心率变化趋势持续增大，表明这种算法模型能够明显区分正常波形与异常波形。采用该方法能及时反映变流器健康状态，可以有效避免由于IGBT故障而导致电力电子系统关闭或损坏的情况。

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高晨（1991），男，博士，工程师，主要研究方向为风电机组设备状态评估，gaochen@tpri.com.cn。

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高晨（1991），男，博士，工程师，主要研究方向为风电机组设备状态评估，gaochen@tpri.com.cn。

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