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Subject: search.filters.subject.discrete wavelet transform

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    Behaviour analysis of H-bridge high-voltage capacitor banks fault on 230-kV substation using discrete wavelet transform
    (2023-11-01)
    Chiradeja, Pathomthat
    ;
    Lertwanitrot, Praikanok
    ;
    Ngaopitakkul, Atthapol
    ;
    Pothisarn, Chaichan
    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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    Discriminating between Capacitor Bank Faults and External Faults for an Unbalanced Current Protection Relay Using DWT
    (2020-01-01)
    Lertwanitrot, Praikanok
    ;
    Ngaopitakkul, Atthapol
    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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    An application of a discrete wavelet transform and a back-propagation neural network algorithm for fault diagnosis on single-circuit transmission line
    (2013-09-01)
    Ngaopitakkul, A.
    ;
    Bunjongjit, S.
    This article proposes an application of the discrete wavelet transform (DWT) and back-propagation neural networks (BPNN) for fault diagnosis on single-circuit transmission line. ATP/EMTP is used to simulate fault signals. The mother wavelet daubechies4 (db4) is used to decompose the high-frequency component of these signals. In addition, characteristics of the fault current at various fault inception angles, fault locations and faulty phases are detailed. The DWT is employed in extracting the high frequency component contained in the fault currents, and the coefficients of the first scale from the DWT that can detect fault are investigated, and the decision algorithm is constructed based on the BPNN. The results show that the proposed technique provides satisfactory results. © 2013 Taylor & Francis Group, LLC.
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    Application of DWT and fuzzy logic algorithm for classifying simultaneous fault types
    (2011-12-01)
    Pothisarn, C.
    ;
    Ngaopitakkul, A.
    This paper proposes a technique using discrete wavelet transform (DWT) and fuzzy logic for identifying types of simultaneous fault along the transmission systems. The PSCAD/EMTDC is used to simulate fault signals. The mother wavelet daubechies4 (db4) is employed to decompose high frequency component from these signals. The coefficients detail (phase A, B, C and zero sequence of post-fault current signals) of DWT at the first peak time that positive sequence current can detect fault, is performed as input variables for the proposed algorithm. The result shows that the proposed technique gives satisfactory accuracy, and will be very useful in the development of a power system protection scheme. © 2011 IEEE.
      1
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    Application of DWt for identifying type of fault occurred in wind turbine system
    (2011-12-01)
    Ngaopitakkul, A.
    ;
    Yodkhuang, A.
    This paper proposes a technique to identify the fault type in the wind turbine system using Discrete Wavelet Transforms (DWT). The fault signals are simulated using PSCAD/EMTDC. The comparisons of the coefficients DWT have been performed in order to classify fault types. The results are shown that the algorithm is capable of performing the fault location as well as the fault types with satisfactory accuracy. © 2011 IEEE.
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    DWT and RBF neural networks algorithm for identifying the fault types in underground cable
    (2011-12-01)
    Ngaopitakkul, A.
    ;
    Pothisarn, C.
    ;
    Bunjongjit, S.
    ;
    Suechoey, B.
    A new technique for classifying fault type in underground distribution system has been proposed. Discrete wavelet transform (DWT) and Radial basis function (RBF) neural network are investigated. Simulations and the training process for the RBF neural network are performed using ATP/EMTP and MATLAB. The mother wavelet daubechies4 (db4) is employed to decompose high frequency component from these signals. Positive sequence current signals are used in fault detection decision algorithm. The output pattern of RBF is divided into two case studies training for comparison between classifying of the fault types and identifying the phase with fault appearance. The variations of first scale high frequency component that detect fault are used as an input for the training pattern. The comparison of the coefficients DWT is also compared with the RBF neural network in this paper. The result is shown that an average accuracy values obtained from RBF gives satisfactory results. © 2011 IEEE.
      2
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    Study of characteristics for simultaneous faults in distribution underground cable using DWT
    (2011-12-01)
    Ngaopitakkul, A.
    ;
    Pothisarn, C.
    ;
    Leelajindakrairerk, M.
    In the literature for fault detection, most of research works have never been mentioned about effects of simultaneous faults. This paper presents behavior of characteristics for simultaneous fault signals in an electrical distribution underground cable using wavelet transform. The fault signal is simulated using ATP/EMTP, and the behavior analysis of signals is performed using discrete wavelet transform (DWT). The DWT is used to detect the high frequency components. The results obtained from the analysis will be useful in the development of a detect fault scheme for electrical distribution underground cable in the future due to an effect of the other fault that occurs at the other side of the system; this leads to the malfunction of the protective relays. © 2011 IEEE.