基于广域测量类噪声信号的节点间振荡相位辨识

Identification of oscillation phase relationship among nodes based on wide area measured ambient signals

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,节点间相位关系是表征系统振荡特性的重要参数之一。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,提出采用自回归滑动平均法对这种类噪声信号进行处理。基于ARMA模型对应Green函数系数与低频振荡模态之间的比例关系,实现对节点间相位关系的估计。将该方法用于对新英格兰系统仿真数据进行处理,辨识结果与小干扰稳定计算结果一致,并进一步将该方法用于处理南方电网实测数据,证明其能有效辨识节点间振荡相位关系。

The weakly damped low frequency oscillation is one of the main factors that influence the stable operation of interconnected power grids.The phase relationship among different nodes is a key characteristic of low frequency oscillation.Small fluctuations caused by random changes of loads exist continuouly in power grids,which can also be called ambient signasl.In this paper,the ARMA method was used to process the ambient signals.According to the relation between the Green function parameter of the ARMA model and the mode shape,the phase relationship between nodes was estimated.The method was used to analyze the stimulation data from New England system,with the results being consistent with the small signal stability calculation results.The approach was then used to process the measured ambient signals in China Southern Power Grid,which validates its feasibility.