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Power System Frequency Estimation Using Adaptive Accelerated MUSIC
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DOI：10.1109/TIM.2018.2826182.png)
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Abstract
En 中文
Frequency estimation is vital for monitoring, control, and protection of power systems. Multiple signal classification (MUSIC) method has been used for frequency estimation in communication systems. This method requires wide range of frequency scanning and heavy computations, which is inappropriate for power system applications. This paper proposes an adaptive accelerated MUSIC algorithm for frequency estimation in power systems. The algorithm accelerates the frequency scanning and adapts itself to transient conditions of power systems, to keep the accuracy of the frequency estimation with minimum computations. Experimental signals besides several static and dynamic test signals are used to evaluate and compare the performance of the proposed algorithm with recent methods. These comparisons show that the proposed algorithm provides faster convergence speed, lower computation burden, and more robustness to noise and grid disturbances. These significant advantages make the proposed algorithm appropriate for power system protection and control applications.
Keywords:
Autocorrelation matrix
eigenvalue
eigenvector
frequency estimation
multiple signal classification (MUSIC)
Pisarenko harmonic decomposition (PHD)
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