A Hybrid Method for Power System Frequency Estimation

Power system frequency is a critical parameter of voltage and current measurements for many applications, such as power quality, monitoring, and protection. This paper presents a hybrid approach for frequency estimation based on Taylor series expansion and Fourier algorithm. The method is derived using a dynamic signal model with varying parameters. The changing envelope of a power signal within an observation data window is approximated with a second-order Taylor series. A Fourier algorithm-based method is proposed to compute the parameters of such signal model. The algorithm using the linear model approach aimed at alleviating the computational complexity is also presented. The comparison of the performance under various conditions between the two approaches is conducted. Inheriting from the use of Fourier algorithm, this hybrid algorithm is immune to power system harmonics. It achieves excellent performance for signals with dynamic variations. The performance is investigated and compared with other techniques through simulations for various scenarios observed in real power systems. Experimental studies demonstrate the advantages of the proposed algorithm.