利用随机响应的低频振荡模式估计方法比较分析

Comparison analysis for low-frequency oscillation mode estimation method using stochastic responses

电力系统随机响应中蕴含着低频振荡模式信息。比较了自相关分析、自然激励技术和随机减量技术等三种方法从随机响应中提取系统自由振荡响应的应用,然后结合特征系统实现算法估计振荡模式频率和阻尼比。通过四机两区域系统和新英格兰系统的蒙特卡洛仿真,从时间窗长、噪声水平、模式阻尼状态及多通道随机响应的模式估计方面,对比分析了三种方法的估计性能和适用性。仿真结果表明,基于自相关分析的自由振荡响应提取方法具有更好的适应性,模式估计精度优于基于自然激励技术和随机减量技术的估计方法。

Stochastic responses in power systems contain mode information of low-frequency oscillations. This paper compares three methods： Auto-Correlation analysis （AC）, Natural Excitation Technique （NEXT） and Random Decrement Technique （RDT）, which are applied to extract system free oscillation response from stochastic response, and then estimates mode frequencies and damping ratios using Eigensystem Realization Algorithm （ERA）. Monte Carlo simulations are carried out in the four-generator two-area system and the New England system, and the estimation performance and applicability of the three methods are compared and analyzed from the aspects of length of time window, noise level, mode damping condition and multi-channel stochastic responses. Simulation results show that the extraction of free response by means of AC has better adaptability, and the mode estimation results are more accurate than the methods based on NExT and RDT.