Maximum-Likelihood Frequency and Phasor Estimations for Electric Power Grid Monitoring

In this paper, new frequency and phasor estimators are presented. These estimators are based on the maximum-likelihood technique and exploit the multidimensional nature of electrical signals. To minimize the likelihood function, we present an optimization algorithm based on the Newton-Raphson technique. While the performance of Fourier-based estimators significantly degrades when the window length is not equal to a multiple of the fundamental half-period, the proposed estimators perform well regardless of the window length. Simulation results show that the proposed estimators clearly outperform the discrete-time Fourier transform in terms of total vector error and frequency error whatever the signal-to-noise ratio, harmonic and interharmonic distortion, and off-nominal frequency deviation are. The benefits of the proposed estimators are also illustrated with real power system data obtained from the DOE/EPRI National Database of power system events.