Subspace-Least Mean Square Method for Accurate Harmonic and Interharmonic Measurement in Power Systems

A high-resolution method for harmonic and interharmonic measurements in power systems is proposed based on the concepts of subspace and least mean square. A subspace function is constructed by using the noise eigenvectors of the autocorrelation matrix of the test signal. The harmonic and interharmonic frequencies of the signal are derived by finding the zeros of the subspace function. A least mean square approach is introduced to compute the amplitudes and phase angles of harmonic and interharmonic components based on the computed frequencies and time-domain measurements of the signal. The proposed method is compared with some of the recently proposed harmonic/interharmonic analysis methods, including discrete Fourier transform (DFT), windowed interpolation DFT, Prony, iterative DFT, and min-norm methods. The effects of noise, fundamental frequency deviation, and subharmonics have been considered. Numerical results show that the proposed method can perform accurate harmonic/interharmonic measurements for power system signals.