电力系统自动化2025，Vol.49Issue(3)：82-92,11.DOI:10.7500/AEPS20240331008
基于实测数据的直驱风电机组谐波特性分析及建模方法
Measurement Data Based Analysis and Modeling Method for Harmonic Characteristics of Direct-drive Wind Turbine
摘要
Abstract
With the development of new power systems,renewable energy represented by wind power generation is widely utilized.Due to the influence of switching characteristics of electronic devices,wind turbines inevitably generate harmonics during the grid connection.During large-scale grid connections,the interaction between wind power cluster devices further exacerbates harmonic issues.Therefore,the measurement data based modeling method for harmonic characteristics of direct-drive wind turbines is proposed,which is used to analyze the harmonic characteristics of wind turbines in engineering practice.Firstly,the key influencing factors of harmonic characteristics at different frequencies are identified,and a harmonic characteristic analysis model for wind turbines is proposed,which simplifies the overall process of harmonic modeling for wind turbines.Secondly,based on the actual topology of wind power clusters,an aggregation harmonic model of wind power clusters is established,which clarifies the interactive effect of harmonics among wind turbines and quantifies the correlation between individual units and clusters considering the coupling effects between wind turbines.Finally,the harmonic characteristics of direct-drive wind turbines are validated by experiments;the accuracy for the aggregated harmonic model of clusters is validated by simulations,and the accuracy of wind power cluster modeling is improved.关键词
新型电力系统/实测数据/直驱风电机组/谐波建模/风电集群Key words
new power system/measurement data/direct-drive wind turbine/harmonic modeling/wind power cluster引用本文复制引用
张磊,孙媛媛,李亚辉,张帆,刘洋,李立生..基于实测数据的直驱风电机组谐波特性分析及建模方法[J].电力系统自动化,2025,49(3):82-92,11.基金项目
国家自然科学基金联合基金重点支持项目(U23B20116) （U23B20116）
国家自然科学基金资助项目(52407120). This work is supported by Joint Funds of National Natural Science Foundation of China(No.U23B20116)and National Natural Science Foundation of China(No.52407120). （52407120）
