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Development of overcurrent relay based on wavelet transform for fault detection in transmission line
(2024-12-01)
Ananwattanaporn, Santipont
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Lertwanitrot, Praikanok
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Ngaopitakkul, Atthapol
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Pothisarn, Chaichan
This study proposes a protection relay using a microcontroller to detect and classify faults in transmission lines based on the wavelet transform. An experimental model was constructed from an actual 115 kV transmission system prototype. The current signal was observed based on the fault type, phase, and position. Clark’s transform and the discrete wavelet transform (DWT) were applied to transform signals for analysis. Moreover, the performance of fault detection based on the output signals of Clark’s transform (alpha sequence, beta sequence, and zero sequence current) was compared to the performance of the alternative proposed fault detection method, which is based on the combining factor between alpha and beta sequence current. In addition, the influence of DWT level on fault analysis is also considered and is used to confirm the accuracy of fault detection. Results show that the proposed method is efficient for fault detection and classification. This finding allows the researcher to choose the appropriate analytical method. Moreover, it can also be used as the basis for overcurrent relay algorithm design in the effort to develop more advanced technologies.
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Artificial Intelligence based Faults Identification, Classification, and Localization Techniques in Transmission Lines-A Review
(2023-12-01)
Kanwal, Shazia
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Jiriwibhakorn, Somchat
An overview of the many methods used for fault detection, classification and location in the power system, particularly in transmission lines, is provided in this review, it also includes an experimental result of adaptive neuro-fuzzy inference system -based fault detection , fault classification and fault location. Being in operation outdoor environment, transmission lines are more vulnerable to various faults which may lead to system collapse in severe cases. Therefore, to ensure the reliable and safe operation of power system it is imperative to critically monitor the faults in transmission lines. In this regard, researchers around the globe have developed several techniques and constantly putting efforts to further improve the protection efficacy. The brief yet thorough analysis and comparison of the artificial intelligence-based techniques, hybrid methodologies and most recent approaches in the context of power system faults have been discussed and presented. In addition, the research work and the experimental results of an adaptive neuro-fuzzy inference system-based techniques have also been discussed for IEEE-9 bus system. The mean square error for testing data of ANFIS-based fault detection, classification, is zero and for fault location Mean square error is 5.32km. This piece of work could be helpful in the development of a comprehensive understanding of various artificial intelligence-based techniques within the realm of fault detection, classification and localization in transmission lines.
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The study on wavelet coefficient behavior of simultaneous fault on the hybrid between overhead and underground distribution system
(2019-05-01)
Pothisarn, Chaichan
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Jettanasen, Chaiyan
This paper proposed the study on behaviour and characteristic of wavelet coefficient in case of simultaneous fault occurrence on hybrid transmission system. The ATP/EMTP software has been used to simulate 115-km hybrid transmission line that modelled after on part of PEA distribution system. The case study system is 40 km distribution line with overhead line on first 20 km section and underground cable on the second half. The Discrete Wavelet Transform (DWT) has been used to analyse fault signal. Various factor that can affect system characteristic such as inception angle, location, and type of fault has been taken into consideration. The result shown the significant change in coefficient of high frequency component when simultaneous fault occurs compared to single fault especially in hybrid distribution system when fault occur on both overhead and underground cable, thus result in problematic analysis of coefficient and complexity in design suitable algorithm. This change in system characteristic must be taken into consideration when develop protection system in order to achieve the satisfactory performance with even more complex power system in the future.
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Discrete wavelet transform for improving the accuracy of an unbalance current protection relay due to transient fault and inrush current signals
(2019-05-01)
Patcharoen, Theerasak
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Ngaopitakkul, Atthapol
An unbalance current protection relay (60C, 51NC) cannot operate fast enough to avoid catastrophic failure against high system fault currents within capacitor units because traditional unbalance current protection relays are not capable of distinguishing and classifying transient fault current and switching inrush current. This paper proposes a new algorithm for the detection and classification of such current signals. The program used for the simulation was PSCAD/EMTDC. The current signals output was used as discrete wavelet transform (DWT) input. The wavelet-based fault and inrush current detection and classification unit received the various captured transient current signals, and used DWT to detect and analyse various cases studies. The actual inrush current signals from both the experimental setup and testing on an actual 115 kV HV shunt capacitor bank were used to verify the proposed algorithm. Results show that the proposed algorithm is effective at accurately identifying fault and inrush currents.
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Application of discrete wavelet transform and back-propagation neural network for internal and external fault classification in transformer
(2019-01-01)
Ngaopitakkul, Atthapol
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Jettanasen, Chaiyan
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Asfani, Dimas Anton
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Negara, Yulistya
This paper proposes an algorithm for internal and external fault discrimination in the three-phase two-winding power transformer based on a combination of discrete wavelet transform (DWT) and back-propagation neural network (BPNN). The maximum ratio obtained from division algorithm between DWT coefficient value of differential current and zero sequence component in post-fault condition differential current signals is employed as an input for the training pattern for BPNN in order to discriminate between internal fault and external short circuit. The proposed algorithm performance has been test using various cases studies based on Thailand electricity transmission and distribution systems data. Results show that the proposed technique can achieved satisfy accuracy for internal and external fault detection and discrimination in the considered system. This methodology and result can be used to further improve protection system of power transformer in the future.
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Application of support vector machines algorithm for discriminating between external fault and internal winding fault in power transformer
(2014-02-04)
Ngaopitakkul, Atthapol
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Jettanasen, Chaiyan
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Leelajindakrairerk, Monthon
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Pothisarn, Chaichan
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Suechoey, Boonlert
The differential relaying principle is used for protection of medium and large power transformers. In the past decade, several decision algorithms have different solutions and techniques. This paper proposes a new technique using discrete wavelet transform (DWT) and support vector machines (SVM) to classify and discriminate between external fault and internal fault in power transformer. The DWT is used to detect the high frequency components from fault signals. The variations of first scale high frequency component that detects fault are used as input for the SVM. The proposed method gives satisfactory accuracy, and will be very useful in the development of a modern protection scheme for electrical power transmission systems. © 2014 ICIC International.
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Identifying types of simultaneous fault in transmission line using discrete wavelet transform and fuzzy logic algorithm
(2013-07-17)
Ngaopitakkul, Atthapol
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Apisit, Chaowat
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Bunjongjit, Sulee
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Pothisarn, Chaichan
In the literature for fault classification, several decision algorithms have different solutions and techniques. These research works have been rarely mentioned about simultaneous faults in transmission systems. This paper presents the decision algorithm for identifying types of simultaneous fault along the transmission line. Decision algorithms based on discrete wavelet transform (DWT) and fuzzy logic are investigated. The analysis of fault signals is performed using DWT. The DWT is used in order to detect the high frequency components. The coefficient details (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, are performed as an input for the fuzzy logic. The result shows that the accuracy of the proposed algorithm is highly satisfactory. © 2013 ICIC International.
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Prediction of fault location in overhead transmission line and underground distribution cable using probabilistic neural network
(2013-01-01)
Chiradeja, P.
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Ngaopitakkul, A.
This paper proposes an algorithm based on a combination of discrete wavelet transform (DWT) and probabilistic neural network (PNN) for locating fault on transmission and distribution system. Simulations and the training process for the PNN are performed using Electromagnetic Transients Program (EMTP) and MATLAB. The mother wavelet daubechies4 (db4) is employed to decompose high frequency component from fault signals. The first peak time in first scale of each bus, that can detect fault, is used as input pattern for the training pattern. Various cases studies based on Thailand electricity transmission and distribution systems have been investigated so that the algorithm can be implemented. The results show that the proposed algorithm is capable of performing the fault location with satisfactory accuracy. © 2013 Praise Worthy Prize S.r.l. - All rights reserved.
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A new content-based medical image retrieval system based on wavelet transform and multidimensional wald-wolfowitz runs test
(2012-12-01)
Nakaram, Phatsarun
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Leauhatong, Thurdsak
Recently, one of the authors proposed a new similarity measure, called weighted multidimensional Wald and Wolfowitz (MWW) runs test, for the content-based color image retrieval system. The algorithm outperforms conventional similarity measures for comparing two color images. In this paper, we propose a new content-based medical image retrieval system based on discrete wavelet transform (DWT) symlet and the weighted MWW runs test. The DWT is used to extracted texture features of the medical images. The weighted MWW runs test is used to compare distributions of texture features of two medical images. Our experiments were performed on 1,000 medical images from image retrieval in medical applications (IRMA). The experimental results show promisingly efficient to retrieve the medical images. ©2012 IEEE.
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The combination of discrete wavelet transform and fuzzy logic algorithm for fault classification on transmission system
(2012-10-01)
Ngaopitakkul, Atthapol
In the literature for fault classification, several decision algorithms have different solutions and techniques. The most research works have only considered the fault diagnosis for single bus systems and two-bus systems. In fact, transmission lines are connected to each other and become a large grid connected system. During faults, it is necessary for the protection system to deal with a complicated transmission network. This paper proposes a new technique using discrete wavelet transform (DWT) and Fuzzy Logic in order to identify the fault types on transmission systems. The DWT is used to detect the high frequency components from these signals. Positive sequence current signals are used in fault detection decision algorithm. The variations of first scale high frequency component that detects fault are used as an input for the fuzzy logic. Various cases studies based on Thailand electricity transmission systems have been investigated so that the algorithm can be implemented. Fuzzy logic is also compared with the comparison of the coefficients DWT technique. The proposed method gives satisfactory accuracy, and will be very useful in the development of a modern protection scheme for electrical power transmission systems. ICIC International © 2012.

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