Statistical Model of Measurement Noise in Real-World PMU-based Acquisitions

Abstract

In this paper, we present a processing technique to determine the statistical distribution of additive measurement noise in real-world acquisitions, with specific reference to Phasor Measurement Unit (PMU) applications in Active Distribution Networks (ADNs). The proposed approach identifies the power signal fundamental component, as well as harmonic and interharmonic interferences, and models the measurement noise as a Gaussian random variable. First, we describe the algorithm main stages and the criteria for the most suitable parameter setting. Then, we carry out a numerical validation inspired by IEEE Std. C37.118.1 test conditions. Finally, we validate the proposed approach on real-world measurements acquired by a PMU in the distribution network of EPFL campus.

A Quantitative Analysis of Wide-Area Phasor Measurement Unit Data

“…To use this approach, the data must be relatively free of events. Frigo et al followed up with a similar work to Brown et al which also sought to determine noise distribution, but through different methodologies [21]. The authors used a methodology that did not require separation of static from dynamic PMU data before extracting noise from the signal, concluding that the noise for their dataset fits additive Gaussian white-noise with SNR close to 45 dB.…”

Supraharmonic Dynamic Phasors: Estimation of Time-Varying Emissions

“…In this sense, the first dataset is derived from point-on-wave data acquired in a real-scale PMU installation on the EPFL campus in Lausanne, Switzerland (dataset available in [32], further details on the measurement setup in [33]). In particular, the dataset refers to a 20-kV substation coupled with a battery energy storage system: medium voltage signals are acquired at Due to the limited sampling frequency, the dataset is not significant for its supraharmonic content, but might be useful to reproduce a realistic time evolution of the fundamental frequency.…”

“…6(a), we reproduce a test condition consisting of a single supraharmonic, whose amplitude is equal to 1 pu and whose frequency is locked to the time evolution of the fundamental frequency with a harmonic order ranging from 40 to 3000. For this analysis, the SNR is set equal to 34 dB, in accordance with the noise levels measured on the real-world dataset [33].…”

PMU-based metrics for Power Quality Assessment in Distributed Sensor Networks

“…1. a normal operating condition with steady-state amplitude and phase, while the frequency varies with a "random walk"-like trend (as measured in the EPFL campus) [21]; 2. an instantaneous frequency step of -2 Hz followed by a steep frequency ramp of 8 Hz/s until coming back to 50 Hz; 3. a signal characterized by phase and amplitude modulations whose period is in the order of 10 s, as inspired by the inter-area oscillation that was recorded in Lausanne in December 2016 [22]; 4. a three-phase fault at the transformer secondary winding (ungrounded terminal) of the bus feeder in the IEEE 34-bus test grid [18].…”