Abstract
In this paper, the adaptive filtering based on LMS algorithm is applied to the recognition of low-frequency oscillation mode. The step factor is improved based on Sinh function to accelerate the convergence speed of the algorithm while ensuring a low steady-state error, and the robustness of the algorithm in identification is improved by combining the maximum correlation entropy rule. The effectiveness of the algorithm for low-frequency oscillation mode identification is verified by simulation of the 10-machine 39-node New-England power system.
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