摘要
基于TEAM(testing electromagnetic analysis methods)Problem 21基准模型,从实验和仿真计算两方面系统地研究多谐波激励下变压器结构件杂散损耗建模与验证方法。考虑线圈涡流损耗的影响,提出一种基于实验更准确地确定结构件杂散损耗的改进方法。搭建硅钢叠片磁、损耗特性测量系统,基于测量数据建立多谐波激励下的损耗模型并予以验证。基于P21C-M1和P21C-EM1模型分别进行谐波激励下导磁和非导磁构件杂散损耗的数值模拟,磁场及损耗结果对比验证了方法的有效性。基于仿真及测量结果,分析谐波对杂散损耗的影响,得到谐波激励下导磁构件中附加损耗的分布及其对杂散损耗的影响。
Based on the testing electromagnetic analysis methods(TEAM)Problem 21 benchmark mode,the modeling and verification of stray-field losses inside structural parts of power transformers under multi-harmonic excitation were investigated systematically from the perspective of experiments and simulations.An improved method was presented to more accurately determine the stray-field losses of structural parts,considering the influence of eddy currents in exciting coils.A measuring system for magnetic properties and losses of silicon steel lamination was designed to identify and verify the loss model applicable for harmonic magnetizations.Numerical simulation was performed on P21C-M1 and P21C-EM1 benchmark models to obtain the stray-field loss of magnetic and nonmagnetic component under harmonic magnetizations,respectively.Filed and loss comparison between experiments and simulations verified the modeling method.The measured and computed results were used to analyze the influence of harmonic on stray-field losses,and obtain the distribution of additional iron losses as well as its contribution to stray-field loss inside magnetic components.
作者
赵小军
王佳雯
刘洋
刘兰荣
程志光
ZHAO Xiaojun;WANG Jiawen;LIU Yang;LIU Lanrong;CHENG Zhiguang(Department of Electrical Engineering,North China Electric Power University,Baoding 071003,Hebei Province,China;State Key Laboratory of Advanced Transmission Technology(Global Energy Interconnection Research Institute Co.Ltd.),Changping District,Beijing 102211,China;Hebei Provincial Key Laboratory of Electromagnetic&Structural Performance of Power Transmission and Transformation Equipment(Preparatory),Baoding 071003,Hebei Province,China)
出处
《中国电机工程学报》
EI
CSCD
北大核心
2020年第2期652-663,共12页
Proceedings of the CSEE
基金
国家重点研发计划资助项目(2017YFB0902703)
国家自然科学基金项目(51777073)
中央高校基本科研业务(2019MS078).