Article(id=1284794222779797671, tenantId=1146029695717560320, journalId=1283840536528293913, issueId=1284794217658560734, articleNumber=null, orderNo=null, doi=10.19912/j.0254-0096.tynxb.2024-2348, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1734451200000, receivedDateStr=2024-12-18, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1784248413032, onlineDateStr=2026-07-17, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1784248413032, onlineIssueDateStr=2026-07-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1784248413032, creator=13701087609, updateTime=1784248413032, updator=13701087609, issue=Issue{id=1284794217658560734, tenantId=1146029695717560320, journalId=1283840536528293913, year='2026', volume='47', issue='6', pageStart='1', pageEnd='814', issueExtLink='null', onlineDate='null', pubDate='1783180800000', pubDateStr='2026-07-05', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1784248411812, creator='13701087609', updateTime=1784252840208, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1284812791785689442, tenantId=1146029695717560320, journalId=1283840536528293913, issueId=1284794217658560734, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1284812791785689443, tenantId=1146029695717560320, journalId=1283840536528293913, issueId=1284794217658560734, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=221, endPage=229, ext={EN=ArticleExt(id=1284794223044038825, articleId=1284794222779797671, tenantId=1146029695717560320, journalId=1283840536528293913, language=EN, title=RAPID ITERATIVE OPTIMIZATION DESIGN OF WIND TURBINE CONVERTER IGBTS BASED ON IMPROVED NSGA-Ⅱ ALGORITHM, columnId=null, journalTitle=Acta Energiae Solaris Sinica, columnName=null, runingTitle=null, highlight=null, articleAbstract=Insulated-gate bipolar transistor （IGBT） modules, as the core power components of wind turbine power converters, are crucial for achieving high operational efficiency and cost-effectiveness. Optimizing the electrical conductivity and manufacturing cost of these modules is essential. However, the demanding operational environments often cause performance degradation, and traditional design optimization methods incur high computational costs, making rapid iterative optimization difficult. To address these limitations, this study proposes a rapid iterative design optimization method for wind turbine converter IGBTs based on an improved NSGA-Ⅱ algorithm （Non-dominated Sorting Genetic Algorithm Ⅱ）. Firstly, the optimization problem is formulated with electrical conductivity and manufacturing cost as dual objectives. A parametric thermoelectric coupling model is developed to enable accurate and efficient evaluation of conductivity under varying design conditions. To further enhance the optimization process, an improved NSGA-Ⅱ algorithm based on kernel density estimation is proposed, significantly improving computational efficiency and optimization accuracy compared to traditional optimization algorithms. Additionally, a Kriging-based surrogate model is employed to construct high-fidelity mappings between design variables and optimization objectives, thereby reducing computational burdens and enabling rapid iterative optimization. Numerical experiments confirm the effectiveness and robustness of the proposed method, demonstrating reductions in electrical losses of up to 20.00% and decreases in manufacturing costs by as much as 27.63%. This study provides a practical and efficient design framework for IGBT modules, offering valuable insights into multi-objective optimization in the field of power electronics. By integrating advanced optimization algorithms with surrogate modeling, the proposed method addresses key challenges in the design and performance enhancement of wind turbine power systems., authors=Fan Jia¹, Zhao Feng^2,3, Liu Yifan⁴, Yang Fan^2,3, Yan Jiquan^2,3, Hu Weifei^2,3, authorsList=Fan Jia, Zhao Feng, Liu Yifan, Yang Fan, Yan Jiquan, Hu Weifei, authorCompany=1. Huadian （Ningxia） Energy Co., Ltd., New Energy Branch, Yinchuan 750002, China;
2. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310058, China;
3. School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China;
4. Huadian Electric Power Research Institute Co., Ltd., Hangzhou 310030, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1284794222968541352, articleId=1284794222779797671, tenantId=1146029695717560320, journalId=1283840536528293913, language=CN, title=基于改进NSGA-Ⅱ算法的风电机组变流器IGBT快速迭代优化设计, columnId=null, journalTitle=太阳能学报, columnName=null, runingTitle=null, highlight=null, articleAbstract=绝缘栅双极型晶体管（IGBT）模块作为风电机组发电系统功率变流器的核心组件,优化其导电性能和制造成本意义重大。为解决这一问题,提出一种基于改进非支配排序遗传算法（NSGA-Ⅱ）的风电机组变流器IGBT模块快速迭代优化设计方法。首先,定义以其导电性能和制造成本为优化目标的优化问题,并构建了参数化热电耦合模型,实现了导电性能的精确快速求解;随后,提出基于核密度估计的改进NSGA-Ⅱ算法,通过与传统优化算法对比,改进算法显著提高了计算效率与优化精度。此外,为减轻计算负担,引入克里金（Kriging）代理模型技术构建了设计变量与优化目标间的高精度代理模型,从而实现了快速迭代优化设计。优化结果表明,该方法最多可将导电损耗减少20.00%,制造成本最多可节约27.63%。, authors=范佳¹, 赵峰^2,3, 刘一凡⁴, 杨凡^2,3, 鄢继铨^2,3, 胡伟飞^2,3, authorsList=范佳, 赵峰, 刘一凡, 杨凡, 鄢继铨, 胡伟飞, authorCompany=1.华电（宁夏）能源有限公司新能源分公司,银川 750002;
2.浙江大学流体动力基础件与机电系统全国重点实验室,杭州 310058;
3.浙江大学机械工程学院,杭州 310058;
4.华电电力科学研究院有限公司,杭州 310030, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=L+VlZ2U7lUvTB28Ex1UndA==, pdfFileSize=3443901, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=国家自然科学基金（52275275）; 浙江省“尖兵”“领雁”研发攻关计划（2023C01008）)}, authors=null, keywords=[Keyword(id=1284813598308418143, tenantId=1146029695717560320, journalId=1283840536528293913, articleId=1284794222779797671, language=CN, orderNo=1, keyword=绝缘栅双极型晶体管), Keyword(id=1284813598383915616, tenantId=1146029695717560320, journalId=1283840536528293913, articleId=1284794222779797671, language=CN, orderNo=2, keyword=风力发电机组), Keyword(id=1284813598455218785, tenantId=1146029695717560320, journalId=1283840536528293913, 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