Wide-band oscillations have become a significant issue limiting the development of wind power.Both large-signal and small-signal analyses require extensive model derivation.Moreover,the large number and high order of ...Wide-band oscillations have become a significant issue limiting the development of wind power.Both large-signal and small-signal analyses require extensive model derivation.Moreover,the large number and high order of wind turbines have driven the development of simplified models,whose applicability remains controversial.In this paper,a wide-band oscillation analysis method based on the average-value model(AVM)is proposed for wind farms(WFs).A novel linearization analysis framework is developed,leveraging the continuous-time characteristics of the AVM and MATLAB/Simulink’s built-in linearization tools.This significantly reduces modeling complexity and computational costs while maintaining model fidelity.Additionally,an object-based initial value estimation method of state variables is introduced,which,when combined with steady-state point-solving tools,greatly reduces the computational effort required for equilibrium point solving in batch linearization analysis.The proposed method is validated in both doubly fed induction generator(DFIG)-based and permanent magnet synchronous generator(PMSG)-based WFs.Furthermore,a comprehensive analysis is conducted for the first time to examine the impact of the machine-side system on the system stability of the nonfully controlled PMSG-based WF.展开更多
基金supported by the National Natural Science Foundation of China under Grant 52277072.
文摘Wide-band oscillations have become a significant issue limiting the development of wind power.Both large-signal and small-signal analyses require extensive model derivation.Moreover,the large number and high order of wind turbines have driven the development of simplified models,whose applicability remains controversial.In this paper,a wide-band oscillation analysis method based on the average-value model(AVM)is proposed for wind farms(WFs).A novel linearization analysis framework is developed,leveraging the continuous-time characteristics of the AVM and MATLAB/Simulink’s built-in linearization tools.This significantly reduces modeling complexity and computational costs while maintaining model fidelity.Additionally,an object-based initial value estimation method of state variables is introduced,which,when combined with steady-state point-solving tools,greatly reduces the computational effort required for equilibrium point solving in batch linearization analysis.The proposed method is validated in both doubly fed induction generator(DFIG)-based and permanent magnet synchronous generator(PMSG)-based WFs.Furthermore,a comprehensive analysis is conducted for the first time to examine the impact of the machine-side system on the system stability of the nonfully controlled PMSG-based WF.
