随机子空间法在低频振荡分析中的应用

摘要

With the development of power system, low frequency oscillations become one of the issues of concern in the stable operation of power system. A stochastic subspace identification (SSI) method was applied to power system low frequency oscillation modes identification in the paper. Based on the state space model, the state matrix is computed by SSI. The signal frequency and damping are obtained by the state matrix eigenvalues and the amplitude and phase of each mode can be acquired by least squares method. A synthetic signal was used to verify its correctness. SSI method and Prony algorithm were compared by use of the simulation data of four machine two area system. Results show that the SSI method is correct, fast and efficient, and it can be applied to low-frequency oscillation on-line monitoring or off-line analysis.%电网规模的日益扩大使得低频振荡成为电力系统稳定运行中备受关注的问题之一,文中将随机子空间法应用于电力系统低频振荡模式辨识.以状态空间模型为基础,通过随机子空间辨识得到系统的状态矩阵,由其特征值可求得信号的频率和阻尼比,再由最小二乘法可得到各分量的幅值和相角.通过一合成信号验证了算法的正确性,再利用四机两区系统的仿真数据,采用随机子空间法和Prony方法分别进行辨识,结果表明,随机子空间法辨识正确,快速有效,可以应用于低频振荡的在线监测和离线分析.