Real-Time B-Spline Interpolation for Harmonic Phasor Estimation in Power Systems

Aleixo, Renato Ribeiro; Lomar, Tiago Da Silva; Silva, Leandro Rodrigues Manso; Monteiro, Henrique Luis Moreira; Duque, Carlos A.

doi:10.1109/tim.2022.3175054

Cited by 8 publications

(3 citation statements)

References 32 publications

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“…While the development of harmonic synchro-phasor estimation technologies is difficult, it is still achievable if the harmonic phasor, e.g., the magnitude and phase of each harmonic component are accurately estimated, especially in situations where there is noise and frequency variation. A preprocessing algorithm for the DFT called B-spline-based interpolation is proposed in [56]. The performance is assessed in terms of total vector error (TVE) and IEEE C37.118.1 and IEC 60255-118-1 standards tests.…”

Section: A Parametric Harmonic Estimation Methodsmentioning

confidence: 99%

A Comprehensive Review of Harmonic Issues and Estimation Techniques in Power System Networks Based on Traditional and Artificial Intelligence/Machine Learning

et al. 2023

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Modern industrial and commercial devices that are fed by power electronics circuits and behave non-linearly tend to produce power quality issues in power systems including harmonics and interharmonics, swell, flicker, spikes, notches, and transient instabilities. Among them, harmonic emission is the most significant challenge to be overcome by the distribution networks. Unwanted current, overheating motors and transformers, equipment failure, and circuit breaker misoperation are some of the harmonic consequences. While it is important to employ the best methods to mitigate or suppress the harmonic distortions in power systems, it is even more essential to estimate these harmonics at the outset by developing smart, efficient, and accurate techniques. Due to their capability for learning, predicting, and identifying, researchers have turned to Artificial Intelligence technologies for harmonic estimation in distribution networks. Although the power system parameters (impedance/admittance model) and many harmonic monitors are prerequisites for traditional harmonic estimation methods, by utilizing Artificial Intelligence, these requirements are minimized. In this paper, a comprehensive review of traditional and modern (smart) harmonic estimation techniques are discussed.

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Section: A Parametric Harmonic Estimation Methodsmentioning

confidence: 99%

A Comprehensive Review of Harmonic Issues and Estimation Techniques in Power System Networks Based on Traditional and Artificial Intelligence/Machine Learning

et al. 2023

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“…Equation (A2), b p (z) −1 is designed as the prefilter. This structure of prefilter can be designed as a finite-impulse response (FIR) filter [24][25][26][27], and the order N = 8 is recommended [24,26].…”

Section: Structure Of the Interpolatormentioning

confidence: 99%

Pseudorange reconstruction for high‐dynamic eLoran signal simulators using B‐spline interpolation

Ma,

Zhao,

et al. 2024

IET Radar Sonar & Navi

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The High‐Dynamic enhanced Loran (eLoran) signal simulator must accurately model the motion parameters and dynamic transmission delays of the carriers in the channel. A method was proposed based on B‐Spline interpolation, capable of arbitrary ratio interpolation and multi‐channel simulation. This method can regenerate carrier‐to‐transmitter distances from available discrete motion asynchronous data, it can effectively reproduce more motion details for carrier. The algorithm can be implemented using digital circuits, allowing for real‐time simulation on a hardware platform. The circuit structure is divided into integer and fractional calculations, which can satisfy the interpolation of asynchronous data with arbitrary ratios. Compared with existing methods, the approach simulates the motion parameters with satisfactory accuracy.

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“…There have been works published on the estimation of harmonic phasors in the form of A h = A h e jφ h , in which the harmonic h amplitude A h , phase φ h , frequency f h , and sometimes ROCOF ROCOF h are the variables of interest [9][10][11][12][13][14][15][16][17]. In [18,19], harmonic phasors are modeled as complex exponential functions and solved via a least-squares approach applied to sampled frequency-domain models of the harmonic phasors.…”

Section: Introductionmentioning

confidence: 99%

Non-Parametric Statistical Analysis of Current Waveforms through Power System Sensors

Wilson

Warmack

Ekti

et al. 2022

Sensors

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The protection, control, and monitoring of the power grid is not possible without accurate measurement devices. As the percentage of renewable energy sources penetrating the existing grid infrastructure increases, so do uncertainties surrounding their effects on the everyday operation of the power system. Many of these devices are sources of high-frequency transients. These transients may be useful for identifying certain events or behaviors otherwise not seen in traditional analysis techniques. Therefore, the ability of sensors to accurately capture these phenomena is paramount. In this work, two commercial-grade power system distribution sensors are investigated in terms of their ability to replicate high-frequency phenomena by studying their responses to three events: a current inrush, a microgrid “close-in”, and a fault on the terminals of a wind turbine. Kernel density estimation is used to derive the non-parametric probability density functions of these error distributions and their adequateness is quantified utilizing the commonly used root mean square error (RMSE) metric. It is demonstrated that both sensors exhibit characteristics in the high harmonic range that go against the assumption that measurement error is normally distributed.

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Real-Time B-Spline Interpolation for Harmonic Phasor Estimation in Power Systems

Cited by 8 publications

References 32 publications

A Comprehensive Review of Harmonic Issues and Estimation Techniques in Power System Networks Based on Traditional and Artificial Intelligence/Machine Learning

A Comprehensive Review of Harmonic Issues and Estimation Techniques in Power System Networks Based on Traditional and Artificial Intelligence/Machine Learning

Pseudorange reconstruction for high‐dynamic eLoran signal simulators using B‐spline interpolation

Non-Parametric Statistical Analysis of Current Waveforms through Power System Sensors

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