基于改进HHT算法的电力系统低频振荡模态辨识研究

Research on Power System Low Frequency Oscillation Modal Identification Based on Improved HHT Method

  • 摘要: 针对电力系统低频振荡问题,在运用阻尼转矩对单机无穷大系统分析低频振荡机理与特点的基础上,对低频振荡经验模态分解时存在的端点效应问题进行了理论分析与改进,提出了一种基于端点优化对称延拓法的有效改进EMD分解边界效应的HHT算法对电力系统低频振荡进行辨识。通过对测试信号进行仿真,同时也利用广域FNET监测系统的测试结果进行低频振荡参数辨识及抑制实验,研究了该算法在模式辨识方面的有效性和准确性。仿真和实验表明,基于改进HHT算法的低频振荡辨识方法能快速高精度地辨识出振荡模态信息,并能有效指导电力系统稳定器PSS的配置及参数设计,从而维持电力系统的安全与稳定。

     

    Abstract: Aimed at the problem of power system low frequency oscillation, based on analyzing of oscillation mechanism and oscillation characteristics with single-machine infinite bus system, this paper proposed an improved HHT algorithm using end optimization symmetric extension method to identify modal parameters of power system low frequency oscillation. Through simulations with testing signal and restraining experiments utilizing wide-area FNET measurement system, the paper also analyzed the effectiveness and veracity of the proposed algorithm. Simulations and experiments showed that the low-frequency oscillation pattern information can be effectively identified based on the proposed HHT algorithm. At the same time, the proposed method is also proved to have a good help to guide the disposition and parameters’ design of power system stabilizer, thereby the safety and stabilization of power system are maintained.

     

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