电力系统自动化2025，Vol.49Issue(23)：68-76,9.DOI:10.7500/AEPS20241113002
构网型双馈风电机组机电耦合特性建模与轴系扭振分析
Modeling of Electromechanical Coupling Characteristics and Analysis of Shaft Oscillation for Grid-forming Doubly-fed Wind Turbine
摘要
Abstract
The doubly-fed wind turbine with grid-forming(GFM)control(GFM-DFIG)can provide active support capability for weak grids.However,GFM control will exacerbate the coupling effect between the mechanical structure of the doubly-fed wind turbine and the grid frequency,increasing the risk of shaft oscillation.At present,when modeling the electromechanical coupling characteristics of GFM-DFIG,on one hand,the influence of the operation region is not considered,and changes in the operation region will directly affect the active power command,resulting in shaft oscillation.On the other hand,when modeling,the regulation effect of the current inner loop on the rotor voltage is usually ignored,and the rotor voltage is affected by both the current loop and the speed loop,which changes the damping characteristics of the shaft oscillation.Therefore,this paper establishes a small-signal model of electromagnetic torque and speed difference,revealing the effects of GFM control parameters,operation region,and current loop parameters on shaft damping.The analysis results indicate that when GFM-DFIG switches operation regions,it will cause shaft oscillation,simply adjusting the GFM control parameters is difficult to solve this problem.Optimizing the current loop bandwidth can effectively reduce the risk of shaft oscillation during the operation region switching process.Finally,the experimental verification is conducted on the hardware-in-the-loop testing platform.关键词
双馈风电机组/机电耦合/构网控制/轴系扭振/小信号模型/电流环Key words
doubly-fed wind turbine/electromechanical coupling/grid-forming control/shaft oscillation/small-signal model/current loop引用本文复制引用
黄旭东,胡彬,赵志坚,占领,张震霄,年珩..构网型双馈风电机组机电耦合特性建模与轴系扭振分析[J].电力系统自动化,2025,49(23):68-76,9.基金项目
国家自然科学基金杰出青年基金资助项目(52325702) （52325702）
浙江省自然科学基金资助项目(LMS25E070001) （LMS25E070001）
中国博士后科学基金第17批特别资助项目(2024T170766). This work is supported by National Natural Science Foundation of China(No.52325702),Zhejiang Provincial Natural Science Foundation of China(No.LMS25E070001)and China Postdoctoral Science Foundation(No.2024T170766). （2024T170766）
