Compressive Sensing of a Taylor-Fourier Multifrequency Model for Synchrophasor Estimation

Abstract

Synchrophasor measurements, performed by phasor measurement units (PMUs), are becoming increasingly important for power system network monitoring. Synchrophasor standards define test signals for verification of PMU compliance, and set acceptance limits in each test condition for two performance classes (P and M). Several PMU algorithms have been proposed to deal with steady-state and dynamic operating conditions identified by the standard. Research and discussion arising from design, implementation, testing and characterization of PMUs evidenced that some disturbances, such as interharmonic interfering signals, can seriously degrade synchrophasor measurement accuracy. In this paper, a new compressive sensing (CS) approach is introduced and applied to synchrophasor measurements using a CS Taylor-Fourier (TF) multifrequency (CSTFM) model. The aim is to exploit, in a joint method, the properties of CS and the TF transform to identify the most relevant components of the signal, even under dynamic conditions, and to model them in the estimation procedure, thus limiting the impact of harmonic and interhamonic interferences. The CSTFM approach is verified using composite tests derived from the test conditions of the synchrophasor standard and simulation results are presented to show its potentialities

Iterative-Interpolated DFT for Synchrophasor Estimation: A Single Algorithm for P- and M-Class Compliant PMUs

“…Several algorithms that compensate the spectral interference generated by the image component of the main tone have been presented in the literature, the majority relying on the IpDFT [7]- [12]. Sine-fitting techniques [13], as well as compressive sensing [14] and lookup tables [15] have been investigated too. In [16] an IpDFT-based method that compensates the spectral interference generated by both the image component of the main tone and harmonic tones is presented.…”

PMU-Based ROCOF Measurements: Uncertainty Limits and Metrological Significance in Power System Applications

“…In this paper, we compare the accuracy and reliability provided by four different ROCOF estimation techniques, based on three consolidated state-of-the-art algorithms, namely the Compressive Sensing-based Taylor-Fourier Model (cs-TFM) [20], the Enhanced Interpolated DFT (e-IpDFT) [21], and the Iterative Interpolated DFT (i-IpDFT) [22]. The proposed analysis enables us to evaluate the ROCOF estimates' dependence from the algorithm parameters, like the adopted signal model and window length.…”

“…In a previous publication [19], we compared the ROCOF estimation accuracy as provided by three window-based algorithms [20]- [22] taken from the recent synchrophasor estimation literature. In this context, we evaluated how static and dynamic signal models represent plausible time-varying ROCOF trends, inspired from real experimental acquisitions.…”

Definition and assessment of reference values for PMU calibration in static and transient conditions

“…The two selected estimation algorithms are the enhanced interpolated DFT (IP-DFT) [7] and the compressive sensing-based Taylor Fourier model (CS-TFM) [8]. They provide a rather comprehensive overview of DFT-based approaches.…”

“…We discuss on the limits of the synchrophasor definition making specific reference to a amplitude step test where we change, intentionally, the dynamic of the event. We compare the response of the NL-LSQ algorithm against two representative PMU algorithms based on Discrete Fourier Transform (DFT) [7], [8], and we propose a time-domain comparison between the PMUestimated phasor and a non-stationary known signal model. The paper is structured as follows: in Section II, after the problem statement, we study the uniqueness, stability and robustness of the solution of the NL-LSQ algorithm; we report in Section III the performance assessment of the algorithm in the static test conditions provided by the IEEE Std; in Section IV, we discuss on the validity of the synchrophasor definition in specific transient conditions and we illustrate an alternative method for the performance assessment of PMUs directly in time domain.…”