中文摘要：

提出一种白噪声激励下的低频振荡模态参数辨识方法,该方法可以代替人工短路和投切电网元件等措施的扰动方式,使辨识过程更加安全经济。首先以白噪声为输入信号,根据输出与输入之间的互相关函数估计脉冲响应函数;然后利用估计的脉冲响应函数,并采用特征系统实现算法辨识电力系统的多输入多输出状态空间模型,进而识别出系统特征值和模态振型向量。在模态参数识别时,虚假模式的产生不可避免,通过对观测量的功率谱分析,可以校验哪些是真实模式,哪些是虚假模式。并以一个4机电力系统的实例仿真检验所提出的方法在每一个步骤的有效性。最后,通过模型交叉确认,进一步证明了辨识得到的状态空间模型是精确的。

英文摘要：

A white noise excitation based identification technique is presented for estimating low-frequency oscillation parameters. The identification process is more safe and economical by using this technique instead of the traditional disturbance method （e. g. artificial fault and adding/removing components of the power network）. First, with white noise excitation, impulse response function can be calculated according to the cross-covariance function of system input and output variables. Then, based on the estimated impulse response function and using ＇eigensystem realization algorithm＇ , a multi-input and multi- output state space model of the power system can be built. Moreover, the eigenvalues and the mode shape of the system are also obtained. It is known that the produce of false modes is impossible to be avoided for any measurement-based method. However, all the true modes and false modes can be distinguished by the analysis of power spectral density of measured data. Third, a simulation for a four-machine power system shows the validity of the method for each step. Finally, through modal cross validation the identified state space modal is further proved to be accurate.