A Phasor Estimation Algorithm based on Hilbert Transform for P-class PMUs

Phasor measurement units (PMUs) are important elements in power systems to monitor and know the real network condition. In order to regulate the performance of PMUs, the IEEE Std. C37.118.1 stablishes two classes—P and M, where the phasor estimation is carried out using a quadrature oscillator and a low-pass (LP) filter for modulation and demodulation, respectively. The LP filter plays the most important role since it determines the accuracy, response time and rejection capability of both harmonics and aliased signals. In this regard and by considering that the M-class filters are used for more accurate measurements, the IEEE Std. presents different M-class filters for different reporting rates (when a result is given). However, they can degrade their performance under frequency deviations if the LP frequency response is not properly considered. In this work, a unified model for magnitude compensation under frequency deviations for all the M-class filters is proposed, providing the necessary values of compensation to improve their performance. The model considers the magnitude response of the M-class filters for different reporting rates, a normalized frequency range based on frequency dilation and a fitted two-variable function. The effectiveness of the proposal is verified using both static and dynamic conditions for frequency deviations. Besides that, a real-time simulator to generate test signals is also used to validate the proposed methodology.

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“…C37.118.1 sets two classes of PMUs [6], that is, P class and M class. Their selection depends basically on the desired application [37]. The Std.…”

Section: Ieee Std C371181mentioning

confidence: 99%

Improved Performance of M-Class PMUs Based on a Magnitude Compensation Model for Wide Frequency Deviations

et al. 2020

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“…PMUs provide a synchronized magnitude and phase estimation under a coordinated universal time (UTC) of an electric signal [24,25]. This signal is determined by:…”

Section: Harmonic Phasor Modelmentioning

confidence: 99%

Harmonic PMU Algorithm Based on Complex Filters and Instantaneous Single-Sideband Modulation

et al. 2019

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Phasor measurement units (PMUs) have become powerful monitoring tools for many applications in smart grids. In order to address the different issues related to harmonics in power systems, the fundamental phasor estimator in a PMU has been extended to the harmonic phasor estimator by several researchers around the world. Yet, the development of harmonic phasor estimators is a challenge because they have to consider time-varying frequencies since the frequency deviation in the harmonic components is proportional to the harmonic order in a dynamic way. In this work, a new algorithm for harmonic phasor estimation using an instantaneous single-sideband (SSB) modulation is presented. Unlike other SSB-based approaches, its implementation in this work is based on concepts of instantaneous phase and instantaneous frequency. In general, the proposed algorithm is divided into two stages. Firstly, the estimation of the fundamental phasor is carried out by means of a complex finite impulse response (FIR) filter which provides the analytic signal used to compute the instantaneous magnitude, phase, and frequency. Secondly, a complex FIR filter bank is proposed for the estimation of the harmonic components, where the instantaneous SSB modulation technique is applied in order to center the harmonic components into specific narrow bands for each complex filter when an off-nominal frequency occurs. The validation of the proposed algorithm is carried out by means of the current standards of phasor measurement units, i.e., Std. C37.118.1-2011 and C37.118.1a-2014, which involve steady-state, dynamic, and time performance tests.

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“…A PMU is an increasingly used monitoring tool in power systems [18]. In general, this tool uses both a phasor estimator to obtain magnitude, phase, and frequency of voltage and current signals, and a global positioning system to synchronize the measurements to an absolute time reference [44,45]. The IEEE Standard C37.118.1 establishes the steady-state and dynamic requirements that have to be achieved by a PMU and presents a reference phasor estimation model that satisfies them [41].…”

Section: Phasor Measurement Unitmentioning

confidence: 99%

“…Then, a demodulation process is carried out using Electronics 2018, 7, 433 4 of 13 two low-pass (LP) filters, resulting in two signals in quadrature, the real one, Re, and the imaginary one, Im. These signals allow the phasor representation of x(t) = X m cos(ωt + θ) as follows [45]:…”

Section: Phasor Measurement Unitmentioning

confidence: 99%

Homogeneity-PMU-Based Method for Detection and Classification of Power Quality Disturbances

et al. 2018

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Over the past few years, power quality (PQ) monitoring has become of paramount importance for utilities and users since poor PQ generates negative consequences. In monitoring, fast detection and accurate classification of PQ disturbances (PQDs) are desirable features. In this work, a new method to detect and classify PQDs is proposed. The proposal takes advantage of the low computational resources of both a phasor measurement unit (PMU)-based signal processing scheme and the homogeneity approach. To classify the PQDs, if–then–else rules are used. To validate and test the proposal, synthetic and real signals of sags, swells, interruptions, notching, spikes, harmonics, and oscillatory transients are considered. For the generation of real signals, a PQD generator based on a power inverter is used. In the proposed method, the PMU information is directly used to classify sags, swells, and interruptions, whereas the homogeneity index is used to distinguish among the remaining PQDs. Results show that the proposal is an effective and suitable tool for PQ monitoring.

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A Phasor Estimation Algorithm based on Hilbert Transform for P-class PMUs

Cited by 10 publications

References 24 publications

Improved Performance of M-Class PMUs Based on a Magnitude Compensation Model for Wide Frequency Deviations

Improved Performance of M-Class PMUs Based on a Magnitude Compensation Model for Wide Frequency Deviations

Harmonic PMU Algorithm Based on Complex Filters and Instantaneous Single-Sideband Modulation

Homogeneity-PMU-Based Method for Detection and Classification of Power Quality Disturbances

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