【摘要】 弱阻尼低频振荡是影响互联电网安全稳定运行的主要因素,振荡模态是表征系统振荡特性的重要参数,反映了各节点对振荡模式的参与情况。目前基于测量信号一般在振荡发生后进行模态分析,缺乏在系统正常运行情况下的分析手段。大量广域实测数据表明,因负荷的随机变化,电网内持续存在类似噪声信号的小幅波动。文中提出一种自回归滑动平均-Prony(ARMA-P)方法对这种类噪声信号进行处理,在采用ARMA模型拟合类噪声信号估计低频振荡模式参数的基础上,进一步建立信号的Prony模型,最终实现对低频振荡模态的辨识。将该方法用于对新英格兰系统仿真数据进行处理,其辨识结果与小干扰稳定计算结果进行了比较,并进一步将该方法用于处理南方电网实测数据,证明了其有效性。更多还原

【Abstract】 The weakly damped low frequency oscillation is one of the main factors that affect the stabile operation of interconnected power grids.Mode shape is a key characteristic of low frequency oscillation.Based on the measured data,mode shape can be identified after the oscillation happened,but the analysis method applicable in steady state is lacking.It has been observed from the wide area measurement data that small fluctuations exist continuously in power grids,caused by random changes of loads,which can also be called ambient signals.A method named auto regressive moving average-Prony(ARMA-P) is proposed to process such ambient signals.Based on the low frequency oscillation mode parameters identified by the ARMA model,the Prony model of ambient signal is further built,then the mode shape can be estimated.This method is used to analyze the simulation data from the New England system,and the result is compared with the small signal stability calculation result.It is further employed to process the measured ambient signals in China Southern Power Grid to validate the feasibility of this method.更多还原