Slow Sampling Online Optimization Approach to Estimate Power System Frequency

摘要

This paper presents a real-time optimization approach based on the Newton-type algorithm (NTA) and the least-squares (LS) method for power system frequency estimation. A nonlinear Newton algorithm is used to track the modulation effect of frequency variation on the online estimation of the phase angle. The LS curve fitting technique extracts the instantaneous power system frequency from the time-varying phase angle estimation by the NTA. A very low sampling rate is adopted to implement the introduced NTA-LS optimization technique. The presented slow sampling NTA-LS approach is a very efficient real-time algorithm which rectifies the need for wide-bandwidth sensors and promises to reduce the hardware complexity in the phasor and frequency measurement applications. The performance of the proposed method is validated by simulations in MATLAB-Simulink. Real-time implementation results are presented which prove robustness and accuracy of the NTA-LS method under time-varying conditions and in the simulated “real-life” field environment.