Instantaneous power quality indices estimation based on operating point fluctuations

With the increasing integration of power electronic converters and renewable energy resources, power system voltage and current waveforms have become increasingly distorted and nonstationary. Rapid tracking of power quality (PQ) indices is crucial for the safe operation of equipment. Conventional Fourier transform (FT)-based methods suffer from limited accuracy under nonstationary conditions because of spectral leakage, while existing time-frequency methods still suffer from limited estimation accuracy and high computational burden. To address these challenges, this paper introduces a conceptual framework termed operating point fluctuations (OPF), in which the time-varying fundamental component is regarded as a dynamic operating point and all distortions are modeled as fluctuations around it. Based on this framework, a set of instantaneous PQ indices is reformulated, and a real-time estimation method is proposed using recursive least squares (RLS) filters and the Hilbert transform (HT). Simulation studies demonstrate that the proposed method achieves high steady-state accuracy, fast dynamic tracking, robustness against a certain degree of frequency estimation error, interharmonics, and noise, and low computational burden. Hardware-in-the-loop (HIL) experiments and field measurement data verification further demonstrate its practical potential.