Transient Inrush and Fault Current Signal Extraction Using Discrete Wavelet Transform for Detection and Classification in Shunt Capacitor Banks

Patcharoen, Theerasak; Ngaopitakkul, Atthapol

doi:10.1109/tia.2019.2963251

Cited by 10 publications

(8 citation statements)

References 7 publications

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“…Moreover, it also identified fault phase. Several capacitor units connecting inside capacitor bank were not obstacles for detecting and identifying faults which are superior to previous research [12][13][14][15][16][17][18][19][20][21][22][23]. • The performances of the proposed method were also verified by comparing the value that is calculated based on the theory of IEEE standard C37.99-2012 [24].…”

Section: Introductionmentioning

confidence: 83%

Behaviour analysis of H‐bridge high‐voltage capacitor banks fault on 230‐kV substation using discrete wavelet transform

Chiradeja,

Lertwanitrot,

Ngaopitakkul

et al. 2023

IET Generation Trans & Dist

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The protection of traditional high‐voltage capacitor banks relies on an unbalance relay which operates when an internal fuse is blown. However, the unbalance relay cannot indicate the cause of the fault. Thus, an operator wastes time and human resources investigating the fault issues. In this paper, a fault which occurred in a 230‐kV power system of Electricity Generating Authority of Thailand was observed by performing simulations using the Power Systems Computer Aided Design (PSCAD) program. The study system based on the double bus station and 72 MVAR capacitor banks was installed in the form of a back‐to‐back topology. Three scenarios were considered: normal condition, fault occurrence in one capacitor bank and fault occurrence in both capacitor banks. Current characteristics such as the current phase and difference in unbalance current were considered. In addition, discrete wavelet transform was applied to solve the ambiguity of current generated from the PSCAD. The authors’ results suggest that identifying fault events using a coefficient of wavelet is more efficient than relying on the current amplitude. The findings mentioned in this paper can be applied in a traditional power system protection scheme to enhance a system's reliability.

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Section: Introductionmentioning

confidence: 83%

Behaviour analysis of H‐bridge high‐voltage capacitor banks fault on 230‐kV substation using discrete wavelet transform

Chiradeja,

Lertwanitrot,

Ngaopitakkul

et al. 2023

IET Generation Trans & Dist

Self Cite

View full text Add to dashboard Cite

show abstract

“…This method was implemented using Daubechies wavelet order 4 (db4) as a mother wavelet due to its commonly used for solving the power system transient issue [33][34][35][36][37][38][39][40][41]. Consequently, the results obtained from the DWT are shown in Figures 13 and 14.…”

Section: Discrete Wavelet Transform (Dwt)mentioning

confidence: 99%

Discriminating Between Capacitor Bank Faults and External Faults for an Unbalanced Current Protection Relay Using DWT

Lertwanitrot

Ngaopitakkul

2020

IEEE Access

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Capacitor faults are a common issue in modern-day power systems. Such systems employ a traditional mechanism that solely relies on unbalanced relays as an indicator of faults in capacitor banks; however, in the case of a relay trip, operators may find it difficult to identify the cause of these faults. To address this issue, this study aims to detect and discriminate between faults in the capacitor bank (i.e., internal faults) and those in the transmission line (i.e., external faults) by employing discrete wavelet transform (DWT). For this purpose, simulations were conducted using PSCAD software and modelled according to the 115-kV system from the Electricity Generating Authority of Thailand (EGAT). Furthermore, case studies involving faults with different phases, side and branch connections, row connections, inception angles, and blown fuses were considered. Moreover, the phase current, unbalanced current, and unbalanced voltage were analyzed to elucidate fault behaviors and the variation in the coefficient obtained via DWT; the unbalanced current and unbalanced voltage were used as design criteria for the proposed detection and relay operation algorithm. Real-world signals were employed to verify the accuracy of the proposed model. The results indicate that the proposed algorithm achieves satisfactory accuracy in terms of fault detection and the operation of relays in capacitor banks. The proposed algorithm is expected to enable an improvement in the performance of protection systems for capacitor banks in the near future.

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“…The identified filter parameters can also be used as information for monitoring the condition of the filter components, thereby preventing possible catastrophic faults [10], [11], [12], [13] and/or parametric faults [14], [15], [16], and thus reducing the failure rate. The entire system will not break down unexpectedly and create unplanned downtime.…”

Section: Introductionmentioning

confidence: 99%

“…The determination of the inductor voltage is obtained by considering the inductance of the output inductor and the coupling inductance. A detection method is proposed in [12] to classify transient fault current and switching inrush current. An overview of different condition monitoring techniques for DC-link capacitors is given in [13], because the capacitor is known to be a reliability critical component [14].…”

Section: Introductionmentioning

confidence: 99%

Experimental Assessment of a Tiny AI-Empowered Output Filter Parameter Extraction Framework for Digital Power

et al. 2023

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An experimental assessment of a ''plug-and-play'' tiny artificial-intelligence-empowered output filter parameter extraction framework for digital power is presented. The framework can be incorporated into an existing digital controller to perform online parameter extraction without adding extra sensors or modifying the power conversion stage. The idea is based on firstly transferring the control from the default control law to the framework, which consists of a predefined control law to perform output regulation for a few switching cycles, then introducing a small-signal perturbation into the control signal, and finally utilizing a long short-term memory (LSTM) network to recognize the dynamic response of the control signal to perform either regression or classification of filter parameters. The LSTM network is trained with a reconfigurable output filter. The proposed framework has been successfully evaluated on a 240W, 100V/48V buck DC/DC converter prototype. The framework's performance is studied by extracting the parameters of a second-order output filter and a fourth-order output filter. For the second-order output filter, the root-mean-square errors (RMSEs) in performing the filter inductor and capacitor regressions are 2.35% and 2.25%, respectively, and the F1-scores in classifying the inductance and capacitance are 0.805 and 0.815, respectively. The framework occupies 0.93% of the memory space of the controller with 512kB flash memories. The extraction time is 17.3ms. For the fourth-order filter, the maximum RMSEs in performing the regression of the filter inductors and capacitors are 2.04% and 6.49%, respectively. The framework occupies 3.62% of the memory space and the extraction time is 328ms.

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Transient Inrush and Fault Current Signal Extraction Using Discrete Wavelet Transform for Detection and Classification in Shunt Capacitor Banks

Cited by 10 publications

References 7 publications

Behaviour analysis of H‐bridge high‐voltage capacitor banks fault on 230‐kV substation using discrete wavelet transform

Behaviour analysis of H‐bridge high‐voltage capacitor banks fault on 230‐kV substation using discrete wavelet transform

Discriminating Between Capacitor Bank Faults and External Faults for an Unbalanced Current Protection Relay Using DWT

Experimental Assessment of a Tiny AI-Empowered Output Filter Parameter Extraction Framework for Digital Power

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