Fault Classification and Section Identification of an Advanced Series-Compensated Transmission Line Using Support Vector Machine

Dash, P.K.; Samantaray, Subhransu Ranjan; Panda, Ganapati

doi:10.1109/tpwrd.2006.876695

Cited by 278 publications

(126 citation statements)

References 11 publications

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“…Recently, SVMs have been used as effective tools for fault classification in power systems [3,8,18,29,32]. This approach constructs the separating hyperplane for pattern recognition.…”

Section: Fault Classification and Faulty Section Identification By Svmsmentioning

confidence: 99%

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A combined protective scheme for fault classification and identification of faulty section in series compensated transmission lines

Çöteli¹

2013

Turk J Elec Eng & Comp Sci

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Abstract:The fault detection process is very difficult in transmission lines with a fixed series capacitor because of the nonlinear behavior of protection device and series-parallel resonance. This paper proposes a new method based on S-transform (ST) and support vector machines (SVMs) for fault classification and identification of a faulty section in a transmission line with a fixed series capacitor placed at the middle of the line. In the proposed method, the fault detection process is carried out by using distinctive features of 3-line signals (line voltages and currents) and zero sequence current. The relevant features of these signals are obtained by using the ST. The obtained features are then used as input to multiple SVM classifiers and their outputs are combined for classifying the fault type and identifying the faulty section. Training and testing samples for the proposed method have been generated with different types of short-circuit faults and different combinations of system parameters in the MATLAB environment. The performance of the proposed method is investigated according to the accuracy of fault classification and faulty section identification. To evaluate the validity of this study, the proposed method is also compared to both ST-neural network and previous studies. The proposed method not only provides a good classification performance for all types of faults, but also detects the faulty section at a high accuracy.

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“…Recently, SVMs have been used as effective tools for fault classification in power systems [3,8,18,29,32]. This approach constructs the separating hyperplane for pattern recognition.…”

Section: Fault Classification and Faulty Section Identification By Svmsmentioning

confidence: 99%

“…Decision tree-based protection schemes were proposed in [17]. The support vector machine (SVM) method was applied for the identification of a faulty section in an advanced SCTL in [3] and [18]. In [19], multiclass SVM and an extreme learning machine were used for fault classification in SCTLs.…”

Section: Introductionmentioning

confidence: 99%

A combined protective scheme for fault classification and identification of faulty section in series compensated transmission lines

Çöteli¹

2013

Turk J Elec Eng & Comp Sci

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“…Neural networks have disadvantages in that they require a considerable amount of training effort to obtain good performance, especially under various operating conditions such as system-loading level, fault resistance, and source impedance. Another disadvantage of neural-based networks is that the results of training may not cover some cases, as the starting point is chosen at random and can end up in minimum times [10][11][12][13]. Wavelet Singular Entropy (WSE) using WT with Singular Value Decomposition (SVD) and Shannon's information entropy theory have been proposed [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Algorithm for Fault Detection and Classification Using Wavelet Singular Value Decomposition for Wide-Area Protection

Lee¹,

Kim²,

Oh³

et al. 2015

Journal of Electrical Engineering and Technology

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-An algorithm for fault detection and classification method for wide-area protection in Korean transmission systems is proposed. The modeling of 345-kV and 765-kV Korean power system transmission networks using the Electro Magnetic Transient Program -Restructured Version (EMTP-RV) is presented and the algorithm for fault detection and classification in transmission lines is developed. The proposed algorithm uses the Wavelet Transform (WT) and Singular Value Decomposition (SVD). The Singular value of Approximation coefficient (SA) and part Sum of Detail coefficient (SD) are introduced. The characteristics of the SA and SD at the fault conditions are analyzed and used in the algorithm for fault detection and classification. The validation of the proposed algorithm is verified by various simulation results.

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“…The simulation results in [14] showed that a network with a TCSC using an FLC had a better response compared to a PID controller. In [15][16][17]19], several fuzzy TCSC damping controllers were designed and investigated to improve power system stability.…”

Section: Introductionmentioning

confidence: 99%

A comparison of fuzzy logic and PID controllers to control transmitted power using a TCSC

Soreshjani¹,

Abjadi²,

Kargar³

et al. 2014

Turk J Elec Eng & Comp Sci

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Nowadays, the use of flexible AC transmission systems (FACTS) is an economical and interesting approach to improve power transfer capability. The thyristor-controlled series capacitor, as a member of the FACTS family, can control interrelated parameters with dynamism due to its ability of rapid control and stabilization. Regardless of all of the works in this area, the control of transmitted power through the design of the firing angle controller is still missing. In this paper, first, the open-loop firing angle controller and its sensitivities are analyzed to fill in this gap. Next, closed-loop controllers such as PID and fuzzy controllers are designed and simulated in MATLAB/Simulink software. Simulation results show that the fuzzy logic controller has a better response, although it is designed with minimum, simple, triangle membership functions and reduced rule bases.

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Fault Classification and Section Identification of an Advanced Series-Compensated Transmission Line Using Support Vector Machine

Cited by 278 publications

References 11 publications

A combined protective scheme for fault classification and identification of faulty section in series compensated transmission lines

A combined protective scheme for fault classification and identification of faulty section in series compensated transmission lines

Algorithm for Fault Detection and Classification Using Wavelet Singular Value Decomposition for Wide-Area Protection

A comparison of fuzzy logic and PID controllers to control transmitted power using a TCSC

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