A New Phasor Estimator for PMU Applications: P Class and M Class

Abstract

Phasor measurement units (PMUs) are fundamental tools in the applications of modern power systems, where synchronized phasor estimations are needed. The accuracy and dynamic performance requirements for phasor, frequency, and rate of change of frequency (ROCOF) estimations are established in the IEEE Std. C37.118.1-2011 along with the IEEE Std. C37.118.1a-2014, where two PMU performances are suggested: P class filters for applications requiring fast response and M class filters for applications requiring high rejection to aliased signals. In this paper, a methodology to design new phasor estimators that satisfy the P class and M class requirements in PMUs is presented. The proposed methodology is based on finite impulse response filters, brick-wall filters, and complex filter design concepts, where frequency range, time performance, harmonic rejection and out-of-band interference requirements are considered in its design. A comparative analysis using the reference model given by the IEEE Std. C37.118.1 is presented. The results show the effectiveness of the phasor estimators under steady-state and dynamic conditions according to the PMU standard, making them suitable tools for applications in power systems.

A Comprehensive review on the current trends in Micro-Phasor Measurement Units

“…C37.118.1-2011 and its amendment) by estimating the frequency, rate of change of frequency and the phasor. This approach implements the FIR filter design throughout the online phasor estimation process thus making this algorithm less complex with simpler computations [8].…”

A SVD-Based Synchrophasor Estimator for P-class PMUs with Improved Immune from Interharmonic Tones

“…Eq. (18) shows that the right singular matrix V of B K is the eigenvector matrix of B T K B K . Then, according to the relationship between eigenvectors and eigenvalues of a Hermitian matrix found by [28], the first row elements in the matrix V, i.e., eigenvectors of the Hermitian matrix B T K B K , can be obtained by…”

“…For example, some algorithms such as a dynamic phasor estimator considering OBI [13], a dynamic phasor model-based method using two digital filters [14], and a symmetric Taylor-based weighted least square algorithm [15] achieved the required accuracy under OBI at the cost of much longer response latency than P-class methods. Moreover, some P+M algorithms use two different configurations to respectively satisfy the P-and M-class PMU requirements, such as the DFT-based adaptive cascaded filters [16], Taylor-Fourier transform algorithm with different window parameters [17], the band-pass synchrophasor filter based on complex brick-wall [18], and synchrophasor filters based on discrete-time frequency-gain transducer [19]. They can realize either fast response for dynamic signal or high accuracy for steady signal, however, these algorithms can not achieve both features at the same time, especially for signals with OBI.…”

Design of Digital Constrained Linear Least-Squares Multiple-Resonator-Based Harmonic Filtering

“…The DFT algorithm has been widely used as phasor estimator due to its simplicity; regrettably, its poor performance under dynamic conditions [23,24] compromises compliance with the standard, leading to the development of new DFT-based algorithms such as interpolated DFT (IpDFT) [25,26]. Additionally, different techniques such as the Taylor series [27], wavelet transform [28], recursive least-squares [29], Kalman filter [15,30], and combined filter design concept [31] have also been proposed to provide solutions that improve the performance presented in traditional DTF-based techniques under dynamic conditions.…”