A hybrid wavelet–APSO–ANN-based protection scheme for six-phase transmission line with real-time validation

Shukla, Sunil; Koley, Ebha; Ghosh, Subhojit

doi:10.1007/s00521-018-3400-x

Cited by 15 publications

(7 citation statements)

References 23 publications

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“…The proposed scheme has been compared with the existing protection schemes reported in the literatures for a six‐phase transmission line on various bases including input signal, input features, nature of loading, adopted technique, tasks performed, statistical analysis, and real‐time validation. Most of the reported protection schemes have adopted the DWT for the extraction of discriminatory attributes from the input signal.…”

Section: Comparison Of Proposed Scheme With Existing Protection Technmentioning

confidence: 99%

“…A common limitation with all these techniques is that none of the techniques cover all the functions of a protection scheme, ie, detection, classification, and location of fault. An artificial neural network has been adopted with discrete Fourier transform, wavelet transform in Koley et al and Koley et al and Shukla et al respectively, for fault detection, classification, and location in six ‐ phase lines.…”

Section: Introductionmentioning

confidence: 99%

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Enhancing the reliability of six‐phase transmission line protection using power quality informatics with real‐time validation

Shukla

Koley

Ghosh

et al. 2019

Int Trans Electr Energ Syst

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Summary The increased power demand has motivated the use of a six‐phase transmission line. The acceptance of six‐phase transmission depends on the development of a comprehensive protection scheme. The relatively higher complexity of a six‐phase system, arising from the large number of possible faults, makes the protection task challenging. The intrusion of harmonics resulting from nonlinear loads further adds to the complexity. This paper proposes a data mining‐based protection scheme using power quality informatics of voltage signals for a six‐phase transmission line with nonlinear loading. The scheme has been extensively tested for evaluating its reliability in terms of accuracy, dependability, and security indices. Considering the stochastic nature of fault incidence, efficacy of the proposed approach has also been validated by Monte Carlo simulations. Further, to authenticate the proposed scheme for practical scenarios, implementation and validation of the proposed scheme have been carried out for real‐time environment using an OPAL‐RT digital simulator.

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Section: Comparison Of Proposed Scheme With Existing Protection Technmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Enhancing the reliability of six‐phase transmission line protection using power quality informatics with real‐time validation

Shukla

Koley

Ghosh

et al. 2019

Int Trans Electr Energ Syst

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“…Researchers made a work on fuzzy method to get the faulty location [8], [9] for a SPTS. Further, a research work [10], [11] has been done ISSN: 2252-8938 with real-time validation for solving fault issues in SPTS by Sunil K et al Another scheme by Ebha et al [12], [13] implemented artificial neural network to predict the faults in SPTS.…”

Section: Introductionmentioning

confidence: 99%

Support vector machine based fault section identification and fault classification scheme in six phase transmission line

Kumar¹,

Kumar

Ramesha

et al. 2021

IJ-AI

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The higher complexity of a six phase transmission system (SPTS) construction and the large number of possible faults makes the protection task challenging. Moreover, the reverse & forward path faults in SPTS cannot be detected by traditional relay as it becomes under-reach. In this paper, a support vector machine (SVM) method including Haar wavelets for SPTS fault section identification and fault classification is focused. The positive-sequence component phase angle and currents at middle two buses are used to formulate a suggested method. Feasibility of suggested SVM is tested with a 138 kV, 300 km, 60 Hz, SPTS in MATLAB based Simulink platform. Several major parameters including far end and near end location conditions are taken to investigate the reach setting and accuracy of proposed SVM. This relaying method can detect the existence of fault in reverse & forward path in 1 ms time.

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“…A high speed travelling wave-based fault detector, classifier and faulty phase selector for a six-phase transmission line has been proposed by Mansour et al [16]. In [17,18], protection of a six-phase line was achieved using an artificial neural network (ANN). Despite the ability to perform the fault detection and classification task quite accurately, the main disadvantage associated with the ANN-based scheme is the requirement of substantial training data for improved performance.…”

Section: Introductionmentioning

confidence: 99%

Protection of six-phase transmission line using recursive estimation of non-linear autoregression model coefficients and decision tree

Althi

Koley

Ghosh

2020

IET Science, Measurement &Amp; Technology

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Ever-increasing energy demands and limited right of way over land motivates the adoption of six-phase power transmission. However, the wider recognition of six-phase transmission necessitates the development of a reliable protection system. Soaring assimilation of non-linear loads has complicated the protection task due to the intrusion of harmonics. This work aims at imparting necessary protection to six-phase transmission systems with immunity against harmonics. The issue pertaining to harmonics and sensor noise-induced non-linearity in the signal being fed to the protective relays has been addressed by modelling the current-voltage profile using a non-linear autoregression approach. Conventional relays are known to malfunction during non-linear loading and noisy measurement. In this context, an adaptive window-based approach has been employed to capture the non-linear dynamics, followed by mapping the model coefficients with the state of the six-phase system using decision trees. The inclusion of parameters in the non-linear auto regressive model for representing harmonic intrusion and noise imparts necessary robustness to the proposed protection scheme against non-linear loading and noisy sensor measurement. The appropriateness of the non-linear autoregression-based scheme has been tested for varying fault scenarios by considering wide variation in the fault attributes, non-linear loading, and noise level in the sensor measurement.

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A hybrid wavelet–APSO–ANN-based protection scheme for six-phase transmission line with real-time validation

Cited by 15 publications

References 23 publications

Enhancing the reliability of six‐phase transmission line protection using power quality informatics with real‐time validation

Enhancing the reliability of six‐phase transmission line protection using power quality informatics with real‐time validation

Support vector machine based fault section identification and fault classification scheme in six phase transmission line

Protection of six-phase transmission line using recursive estimation of non-linear autoregression model coefficients and decision tree

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