IEEE Trans. Ind. Electron.

2023

DOI: 10.1109/tie.2022.3181362

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Extremum Seeking as a Tool for Active Damping of Active Front-End Converters

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A Harmonic Mitigation Techniques At Unit Level1

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Cited by 7 publications

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“…Fig. 10 (a) corresponds to the experimental results of the time domain grid current waveform of a damped AFE proposed in [32]. Fig.…”

Section: A Harmonic Mitigation Techniques At Unit Levelmentioning

confidence: 99%

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

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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.

“…Fig. 10 (a) corresponds to the experimental results of the time domain grid current waveform of a damped AFE proposed in [32]. Fig.…”

Section: A Harmonic Mitigation Techniques At Unit Levelmentioning

confidence: 99%

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

¹

,

²

,

³

et al. 2023

Self Cite

View full text Add to dashboard Cite

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.

A novel suppression strategy of frequency coupling oscillation for grid-connected VSI-based systems

Yang,

Huang,

Xu

et al. 2024

International Journal of Electrical Power & Energy Systems

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A Simple Proportional Resonant Current Controller with Floor Function Modulation Strategy For a Three-Phase, Three-Level Reduced Component Count Based Active Front-End Converter

Bhanuchandar,

Murthy

2023

2023 IEEE 20th India Council International Conference (INDICON)

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No abstract

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