基于已知激励响应的低频振荡信息在线辨识

当前电力系统常采用日常小扰动响应在线辨识获取低频振荡模式信息，这对大电网低频振荡的分析和抑制具有重要价值。针对低频振荡信息在线辨识，给出了两段最小二乘法，与常规递推自回归滑动平均方法相比，其具有较高的迭代收敛速度与辨识准确度。在介绍小扰动下的已知激励响应信号和环境激励响应信号基本原理的基础上，对比得出2种信号在激励与响应、信号成分和数据量大小方面存在的区别，提出低频振荡在线模式信息辨识方案，进一步在10机39节点系统中通过仿真获取已知激励响应信号和环境激励响应信号，对2种信号的功率谱与辨识结果进行对比分析。分析结果表明在确定激励位置、观测点选择和响应模式间对应关系时已知激励响应信号的辨识效果更好，在该情况下可以将已知激励响应辨识作为低频振荡信息在线辨识的主要手段。

Online identification of low-frequency oscillation information based on known excitation response

Current power system often uses online identification based on daily small disturbance response to obtain low-frequency oscillation mode information, which is of great value for the analysis and suppression of low-frequency oscillation in large power grid. As for the online identification of low-frequency oscillation information, the two-stage least squares estimation method is provided. Compared with the conventional recursive auto-regressive moving average method, it has the virtue of higher iterative convergence speed and better identification accuracy. Based on introducing the basic principles of the known excitation response signal and the environment excitation response signal under small disturbance, the differences between the two signals from aspects of excitation jointly with response, signal component and data volume are compared and obtained. Meanwhile, the online mode information identification scheme of low-frequency oscillation is proposed. Furthermore, the known excitation response signal and environmental excitation response signal are obtained by the simulation in 10-machine 39-bus system. The power spectrum and the identification results of the two signals are analyzed and compared. The analysis results show that when the corresponding relationship between the excitation position, the selection of observation points and the response mode are determined, the known excitation response signal identification has better performance. In this case, the known excitation response identification can be used as the main means for the online identification of low-frequency oscillation information.