Enhanced IpD2FT-Based Synchrophasor Estimation for M Class PMUs Through Adaptive Narrowband Interferers Detection and Compensation
Xuansheng Shan, David Macii, Dario Petri, He Wen
Abstract
One of the most challenging problems in the design of next-generation phasor measurement units (PMUs) is related to the need to minimize the impact of multiple harmonics and out-of-band interferers (OOBIs) on the measurement of synchrophasors over short observation intervals. Most of the existing solutions aim at removing such narrowband disturbances before synchrophasor estimation. However, when data records are short, accurate OOBI filtering may be infeasible. The algorithm described in this article tackles this problem through a prior estimation of the number and the frequency of the significant narrowband interferers emerging from the noise floor. This result is achieved using a nonparametric signal detector based on random matrix theory and hypothesis testing, followed by the application of the estimation of signal parameters via the rotational invariance technique (ESPRIT). Once the number and the frequency of the narrowband components are known, these parameters are used to augment the dimension of the frequency-domain linear system of equations employed by the interpolated dynamic discrete Fourier transform (IpD2FT) for synchrophasor estimation. The results of multiple simulations confirm that not only the proposed approach for narrowband components detection is robust and more accurate than other model-order estimation algorithms described in the scientific literature, but also the synchrophasor estimation accuracy over two-cycle observation intervals is generally higher than using other for M Class PMUs algorithms when OOBIs or a mixture of OOBIs and harmonics are considered.