Highly accurate frequency estimation for FNET

Frequency disturbances is one of the most important indicator that reflects the state of an electrical power system. Making accurate frequency measurement from low voltage distribution systems through the wide deployment of Frequency Disturbance Recorders (FDRs) has been the major innovation for the Frequency monitoring network (FNET). Currently, the frequency calculation algorithm based on the phasor angles (FPA) of the measured voltage signal in the FDR, has achieved high accuracy. However, this algorithm is very sensitive to noise which is inevitable in the signal sampling process. As a result, the frequency estimation accuracy will be degraded if the measured signal is not clean enough. Therefore, to achieve even more accurate and robust frequency estimation from the measured voltage signal, a novel algorithm is proposed in this paper consisting of two stages of operations. The first stage applies a band pass filter that eliminates the irrelevant harmonics; while the second stage removes the noise within the pass band and estimates the frequency fluctuation simultaneously based on the least squares nonlinear curve fitting. The experiments based on synthetic data and real data validates the effectiveness of the proposed method for improving the accuracy of frequency estimation.