An efficient iterative optimization-based algorithm for the real-time estimation of harmonics under power system frequency deviations

In current electrical power industry, a great number of power electronic devices produce harmonics. Moreover, the fundamental system frequency of a power line can deviate in the cases of fluctuating and periodically varying loads and transients. This frequency deviation introduces further undesirable frequency components in the spectrum. Correct measurement of harmonics under such system frequency deviations has prominent importance for the protection of power electronics devices. For this goal, this paper proposes a new iterative optimization-based algorithm for the estimation of harmonics in these circumstances. The method is based on time-domain Gauss-Newton optimization of distorted power line signal which attains its parameters directly from the spectrum of the signal by employing local extrema of the corresponding spectrum. In the first phase of the algorithm, the deviated system frequency is estimated. In the second phase, the harmonic components are estimated and fine-tuned correspondingly. Case studies show that the proposed method is robust and precisely estimates deviations in the system’s fundamental frequency and measure the amplitudes of harmonic components very accurately. It requires just a stoppage criterion. The computational assessment of the method also shows its time efficiency in identifying harmonics. Thus, it is a very good candidate for real-time harmonic measurements.