基于Rife-Vincent窗和同步相量测量数据的风电次同步振荡参数辨识

随着电网中风力发电渗透率的增加,电力系统发生次同步振荡(sub-synchronous oscillation,SSO)的可能性显著增加,报道显示次同步振荡给电力系统设备安全和稳定运行带来重大挑战,如何准确地辨识SSO参数对抑制SSO至关重要。为了利用同步测量数据并提高计算精度,减少频谱泄漏和栅栏效应对辨识的影响,提出一种利用复数域同步相量数据的SSO关键参数辨识方法。首先,通过频谱分析得到复数域含SSO信号加窗同步相量的表达式,并推导得到系统基频分量和SSO分量在频域中的特征;然后基于加阻尼Rife-Vincent窗和三点插值法计算出复数域下SSO的频率、阻尼系数、幅度和相位参数。通过辨识不同条件下的仿真信号验证所提方法的有效性。仿真结果表明,相对于传统方法,该方法能更好地抑制频谱泄露和栅栏效应,具有更高的计算精度和鲁棒性。

Parameter Identification of Wind Power Sub-synchronous Oscillation Based on Rife-Vincent Window and Synchrophasor Data

The probability of sub-synchronous oscillation(SSO)has increased significantly with the growing penetration of wind power generation in power system.SSO has been reported that it brought major challenges to the safe and stable operation of power system equipment.How to accurately identify SSO parameters is extremely important to suppress SSO.To utilize synchronized measurement data and improve the calculation accuracy and reduce the influence of spectrum leakage and fence effect on identification,this paper proposed an innovative identification method of SSO key parameters using complex-domain synchrophasor data.First,the expression of windowed phasor with SSO signal in complex number domain was obtained through spectrum analysis,and the characteristics of system fundamental frequency component and SSO component were derived in frequency domain.Then based on damped Rife-Vincent window and three-point interpolation method the frequency,damping factor,amplitude and phase parameters of SSO were calculated in the complex domain.The effectiveness of the proposed method was verified by identifying simulated signals under different conditions.The simulation results show that,compared with the traditional method,the proposed method can better suppress the spectrum leakage and fence effect,and obtain higher calculation accuracy and robustness.