基于模糊滤波和Prony算法的低频振荡模式在线辨识方法

考虑到Prony算法对输入信号要求较高、对分析数据的噪声非常敏感，提出一种模糊滤波和Prony算法相结合的电力系统在线低频振荡模式的辨识方法。该方法以广域测量信号作为输入，通过简单的模糊逻辑推理快速对输入信号进行滤波，利用Prony算法对滤波后的数字信号进行分析后在线获得电力系统低频振荡的模式。以华中电网支路302245上的有功功率振荡分析为例，通过对模糊滤波前后的输入信号进行比较以及对传统Prony算法和考虑模糊滤波的Prony算法分别进行低频振荡模式辨识的比较，表明了前置滤波的重要性以及所提出的方法能相对精确地进行振荡模式辨识，验证了其有效性。

An Online Identification Method for Power System Low-frequency Oscillation Based on Fuzzy Filtering and Prony Algorithm

Since Prony algorithm has high requirement to the input signal and sensitive to the noise of analysis data, this paper proposes a fuzzy filtering and Prony algorithm combined online identification method for power system low-frequency oscillation. In the proposed method, the wide area measurement signals are the inputs of a fuzzy filter which can cancel the noise rapidly by simple fuzzy logic, and then the low frequency oscillation modes are obtained online by analyzing the digital signal with the improved Prony algorithm. Simulations on the active power oscillation of branch 302245 of Central China Power Grid (CCPG) and comparisons of the method proposed with the traditional method demonstrate that the proposed method can provide relatively precise analysis results.