Wavelet entropy based fault detection approach for MMC-HVDC lines

Wang, Shuai; Bi, Tianshu

doi:10.1109/pesgm.2015.7286582

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…The WEE measures the energy of the wavelet coefficients at each decomposition scale, and gives the energy distribution of the signal. If different frequency components appear in the content of the signal, higher WEE values are obtained [27]. The unit of WEE is bits since the base of the logarithm is chosen as 2.…”

Section: Wavelet Energy Entropymentioning

confidence: 99%

Determination of Flicker Contribution Level by Using Proposed Index

Silsüpür¹,

Türkay²

2018

ElAEE

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Depending on different load characteristics, various power quality disturbances such as sag-swell, harmonics, inter-harmonics, and flicker, appear in electric power systems. Among these power quality disturbances, the flicker is one of the critical power quality phenomenon due to the lack of source detection and disturbance responsibility sharing method. The measurement of the flicker level is defined in the IEC 61000-4-15 standard by a flicker meter. This meter deals only with voltage signals and is not sufficient to understand the contribution of the load and background power systems separately. Thus, this paper proposes new approaches to the evaluation of flicker characteristics using the real on-site measurements taken from two different iron and steel factories. The novelty of this paper is investigating the flicker characteristics in light of statistical methods, spectral and multi-resolution wavelet analysis, and the information theory based wavelet energy entropy analysis together, and proposing a new index to interpret the flicker responsibility of load and power system. This proposed index is called Flicker Contribution Ratio (FCR) and represents the percentage flicker disturbance responsibility of both load and power system.

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Section: Wavelet Energy Entropymentioning

confidence: 99%

Determination of Flicker Contribution Level by Using Proposed Index

Silsüpür¹,

Türkay²

2018

ElAEE

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“…In [27], wavelet analysis and an improved neural network are used. The authors of [28] use the wavelet energy spectrum entropy to perform a statistical analysis of the energy distribution of the signal in each frequency band. Finally, ref.…”

Section: Introductionmentioning

confidence: 99%

Open-Circuit Fault Detection and Location in AC-DC-AC Converters Based on Entropy Analysis

Morel

Akrad

2023

Energies

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Inverters and converters contain more and more power electronics switches which may subsequently affect their reliability. Therefore, fault detection and location are essential to improve their reliability and to ensure continuous operation. In this paper, an AC−DC−AC converter with three-phase inverter is investigated under permanent, single and multiple open-circuit fault scenarios. Many entropies and multiscale entropies are then proposed to evaluate the complexity of the output currents by quantifying their entropies over a range of temporal scales. Among the multitude of entropies, only some entropies are able to differentiate healthy from open-circuit faulty conditions. Moreover, the simulation results show that these entropies are able to detect and locate the arms of the bridge with open-circuit faults.

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“…Meanwhile, the signal processing algorithms are usually based on traveling wave analysis in which the most relevant features of the signal are extracted using transforms as wavelet transform [37][38][39][40], Fourier transform [41][42][43], and Hilbert transform [44,45]. However, they present some difficulties in the detection of the wave-front due to interference of signals and its dependence on the sampling frequency value [46][47][48].…”

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confidence: 99%

Analysis of Local Measurement-Based Algorithms for Fault Detection in a Multi-Terminal HVDC Grid

et al. 2019

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One of the most important challenges of developing multi-terminal (MT) high voltage direct current (HVDC) grids is the system performance under fault conditions. It must be highlighted that the operating time of the protection system needs to be shorter than a few milliseconds. Due to this restrictive requirement of speed, local measurement based algorithms are mostly used as primary protection since they present an appropriate operation speed. This paper focuses on the analysis of local measurement based algorithms, specifically overcurrent, undervoltage, rate-of-change-of-current, and rate-of-change-of-voltage algorithms. A review of these fault detection algorithms is presented. Furthermore, these algorithms are applied to a multi-terminal grid, where the influence of fault location and fault resistance is assessed. Then, their performances are compared in terms of detection speed and maximum current interrupted by the HVDC circuit breakers. This analysis aims to enhance the protection systems by facilitating the selection of the most suitable algorithm for primary or backup protection systems. In addition, two new fault type identification algorithms based on the rate-of-change-of-voltage and rate-of-change-of-current are proposed and analyzed. The paper finally includes a comparison between the previously reviewed local measurement based algorithms found in the literature and the simulation results of the present work.

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Wavelet entropy based fault detection approach for MMC-HVDC lines

Cited by 5 publications

References 10 publications

Determination of Flicker Contribution Level by Using Proposed Index

Determination of Flicker Contribution Level by Using Proposed Index

Open-Circuit Fault Detection and Location in AC-DC-AC Converters Based on Entropy Analysis

Analysis of Local Measurement-Based Algorithms for Fault Detection in a Multi-Terminal HVDC Grid

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