An Approach Using Support Vector Machines for Distance Relay Coordination in Transmission System

Ravikumar, B; Thukaram, D; Khincha, H.P.

doi:10.1109/tpwrd.2008.2002971

Cited by 29 publications

(7 citation statements)

References 19 publications

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“…The most commonly used kernel functions in power system applications are Linear, Polynomial and Gaussian radial basis functions (RBF) [22,23,[26][27][28][29][30][31][32][33], they can be defined as:…”

Section: Classifications With Svmmentioning

confidence: 99%

A novel protection scheme for synchronous generator stator windings based on SVM

El‐Saadawi

Hatata

2017

Prot Control Mod Power Syst

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This paper proposes a novel scheme for detecting and classifying faults in stator windings of a synchronous generator (SG). The proposed scheme employs a new method for fault detection and classification based on Support Vector Machine (SVM). Two SVM classifiers are proposed. SVM1 is used to identify the fault occurrence in the system and SVM2 is used to determine whether the fault, if any, is internal or external. In this method, the detection and classification of faults are not affected by the fault type and location, pre-fault power, fault resistance or fault inception time. The proposed method increases the ability of detecting the ground faults near the neutral terminal of the stator windings for generators with high impedance grounding neutral point. The proposed scheme is compared with ANN-based method and gives faster response and better reliability for fault classification.

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Section: Classifications With Svmmentioning

confidence: 99%

A novel protection scheme for synchronous generator stator windings based on SVM

El‐Saadawi

Hatata

2017

Prot Control Mod Power Syst

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“…To avoid these problems, fast iterative algorithm like the Sequential Minimal Optimization [29], which is easy to implement is chosen for training the SVM. Recently SVM has been used for many power system applications [20], [21], [23], [30]. The SVM technique was generalized for nonlinear separating surfaces, and it was further extended for constructing decision rules in the non separable case.…”

Section: A Support Vector Machine For Classificationmentioning

confidence: 99%

“…The Principal Component Analysis(PCA) is applied for preprocessing of input data to improve the performance wavelet transform based traveling wave protection [16]. A Hybrid relay proposed for high speed transmission line protection [19] As the pattern recognition approaches can overcome the problems such as fault resistance, fault distance, reactance effect, incomplete knowledge of system parameters , they are widely used in power system fault diagnosis, distance relay coordination, recognition of fault transients, etc [20]- [23]. The speed and accuracy of distance relays of transmission lines can be improved by accurate and fast faulty phase selection, which is the primary requirement for protective relaying to start and trip correctly.…”

Section: Introductionmentioning

confidence: 99%

Support vector machine based high speed protection relay for EHV/UHV transmission line

Ravishankar

Thukaram

2012

2012 2nd International Conference on Power, Control and Embedded Systems

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This paper presents a fast and accurate relaying technique for a long 765kv UHV transmission line based on support vector machine. For a long EHV/UHV transmission line with large distributed capacitance, a traditional distance relay which uses a lumped parameter model of the transmission line can cause malfunction of the relay. With a frequency of 1kHz, 1/4th cycle of instantaneous values of currents and voltages of all phases at the relying end are fed to Support Vector Machine(SVM). The SVM detects fault type accurately using 3 milliseconds of post-fault data and reduces the fault clearing time which improves the system stability and power transfer capability. The performance of relaying scheme has been checked with a typical 765kV Indian transmission System which is simulated using the Electromagnetic Transients Program(EMTP) developed by authors in which the distributed parameter line model is used. More than 15,000 different short circuit fault cases are simulated by varying fault location, fault impedance, fault incidence angle and fault type to train the SVM for high speed accurate relaying. Simulation studies have shown that the proposed relay provides fast and accurate protection irrespective of fault location, fault impedance, incidence time of fault and fault type. And also the proposed scheme can be used as augmentation for the existing relaying, particularly for Zone-2, Zone-3 protection.Index Terms-UHV transmission line protection, Electromagnetic Transients program (EMTP), support vector machine (SVM)

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“…Among these, support vector machines (SVMs) are an important method in the fields of neural networks and nonlinear modeling, and have been successfully applied to problems of classification and nonlinear function estimation [1,2]. The basic technology of SVM, pioneered by Vapnik in 1995, is a state-of-the-art artificial neural network (ANN) based on statistical learning [3,4].…”

Section: Introductionmentioning

confidence: 99%

A Regularized Monotonic Fuzzy Support Vector Machine Model for Data Mining With Prior Knowledge

Li¹,

Chen

2015

IEEE Trans. Fuzzy Syst.

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Incorporating prior knowledge into data mining is an interesting but challenging problem, and this study proposes a novel fuzzy SVM model to explore this issue. It considers the fact that in many applications each input point may not be exactly labeled as one particular class, and thus it applies a fuzzy membership to each input point. It also utilizes expert knowledge concerning the monotonic relations between the response and predictor variables, which is represented in the form of monotonicity constrains. We formulate the classification problem of a monotonically constrained fuzzy SVM, called a monotonic FSVM, derive its dual optimization problem, and theoretically analyze its monotonic property. The Tikhonov regularization method is further applied to ensure that the solution is unique and bounded. A new measure, the frequency monotonicity rate, is proposed to evaluate the ability of the model to retain the monotonicity. The results of the experiments on real-world and synthetic datasets show that this method, which considers different contributions of each data and the prior knowledge of the monotonicity, has a number of advantages with regard to predictive ability and retaining monotonicity over the original FSVM and SVM models when applied to classification problems.

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An Approach Using Support Vector Machines for Distance Relay Coordination in Transmission System

Cited by 29 publications

References 19 publications

A novel protection scheme for synchronous generator stator windings based on SVM

A novel protection scheme for synchronous generator stator windings based on SVM

Support vector machine based high speed protection relay for EHV/UHV transmission line

A Regularized Monotonic Fuzzy Support Vector Machine Model for Data Mining With Prior Knowledge

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