电力系统随机响应的低频振荡模式参数能够反映电网小干扰稳定特性.针对系统正常运行下响应的随机性所引起的振荡模式参数估计的不确定性问题,提出一种同时估计振荡模式参数及其不确定性边界的方法.采用预测误差方法辨识随机响应的自回归滑动平均模型,在此基础上,通过推导自回归模型参数的协方差矩阵与振荡模式参数方差之间的联系,计算低频振荡模式参数及其不确定性边界.通过四阶线性系统和新英格兰系统的蒙特卡罗仿真,对比模式参数的经验样本方差和估计的方差均值,结果表明利用单组数据能够准确估计出模式参数的不确定性边界.最后利用 WECC系统实测数据验证了模式参数及其不确定性边界估计的有效性.“,”The mode parameters of low frequency oscillation obtained from power system stochastic response can indicate the small-disturbance-stability characteristics. To solve the uncertainty problem in parameters estimation of oscillation mode caused by the randomness of response under system normal operation, an oscillation mode estimation method was presented which can estimate both the mode parameters and their uncertainty bounds. The auto-regressive and moving average (ARMA) model of stochastic response was identified by using prediction error method (PEM), and on this basis the relation between the covariance matrix of auto-regressive (AR) model parameters and the variance of mode parameter was derived. The mode parameters and their uncertainty bounds of each mode were calculated. Monte Carlo simulations were carried out in the fourth-order linear system and the New England system, the results of comparison between the means of estimated variance and the empirical sample variances of mode parameters show that it is feasible to estimate the uncertainty bounds of mode parameters using single set of signal. Finally, the filed signal in WECC system was utilized to demonstrate the effectiveness of the estimation of mode parameters and their uncertainty bounds.