A fault classification technique for transmission lines using an improved alienation coefficients technique

Samet, Haidar; Shabanpour-Haghighi, Amin; Ghanbari, Teymoor

doi:10.1002/etep.2235

Cited by 11 publications

(9 citation statements)

References 28 publications

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“…As mentioned earlier, the performance of conventional protection schemes degrades during wide variation in the nonlinear loading condition, because of power quality issues. The power swing arising due to the load variation may also affect the selectivity and sensitivity of distance relay . To evaluate the performance of the proposed protection scheme in detecting and classifying a fault under varying loading condition, cases involving both variation in load (+40% to −40%) and fault have been simulated and efficacy of the proposed scheme evaluated for these cases.…”

Section: Performance Analysis and Discussionmentioning

confidence: 99%

“…The power swing arising due to the load variation may also affect the selectivity and sensitivity of distance relay. [28][29][30] To evaluate the performance of the proposed protection scheme in detecting and classifying a fault under varying loading condition, cases involving both variation in load (+40% to −40%) and fault have been simulated and efficacy of the proposed scheme evaluated for these cases. The test results depicted in Tables 4 and 5 confirm the accuracy and reliability of the proposed scheme under wide variation in linear and nonlinear loading conditions of the transmission line.…”

Section: Line Loading Variationmentioning

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: Performance Analysis and Discussionmentioning

confidence: 99%

Section: Line Loading Variationmentioning

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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“…This technique is capable of classification using only three-phase current waveforms and its delay time is half cycle of power frequency. Also, another version of this approach is presented in [29]. The performance of the proposed method is compared with the above-mentioned methods based on following factors; the results are tabulated in Table 8 The number of the whole cases considered in this Section is 410; 200 cases for different fault resistances and inception instants, 50 cases for different fault locations, 70 cases for different sources X/R ratios, 50 cases for different sources angles, and 40 cases for different short circuit levels.…”

Section: A Comparison With Other Techniquesmentioning

confidence: 99%

k-NN based fault detection and classification methods for power transmission systems

Majd

Samet

Ghanbari

2017

Prot Control Mod Power Syst

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This paper deals with two new methods, based on k-NN algorithm, for fault detection and classification in distance protection. In these methods, by finding the distance between each sample and its fifth nearest neighbor in a predefault window, the fault occurrence time and the faulty phases are determined. The maximum value of the distances in case of detection and classification procedures is compared with pre-defined threshold values. The main advantages of these methods are: simplicity, low calculation burden, acceptable accuracy, and speed. The performance of the proposed scheme is tested on a typical system in MATLAB Simulink. Various possible fault types in different fault resistances, fault inception angles, fault locations, short circuit levels, X/R ratios, source load angles are simulated. In addition, the performance of similar six well-known classification techniques is compared with the proposed classification method using plenty of simulation data.

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“…Methodology using phase angles and algorithm based on energy function is implemented 21 for detection and mitigation of angle instability. Statistical behaviour of transmission line currents is used for event detection and classification by improved alienation coefficients technique 22 . However, it does not identify location of events.…”

Section: Introductionmentioning

confidence: 99%

A new synchronized data‐driven‐based comprehensive approach to enhance real‐time situational awareness of power system

Shrivastava

Siddiqui

Verma

2021

Int Trans Electr Energ Syst

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Summary Identification of disturbances that pushes the power system towards insecure limits can assist in timely remedial measures to be taken for improving situation awareness. The information about event's signature is primarily available in the form of frequency or voltage signals obtained from phasor measurements units (PMUs) in real‐time. Proper evaluation of power system event characteristics enhances the situational awareness and assists system operator to develop required corrective measures for secure operations. In this paper, a fast and accurate algorithm is proposed to identify, classify and locate the events using minimum synchronized data for enhancing the situational awareness of the system. An index is developed with short window synchronized bus frequency data of 18 cycles to detect an event in the network. For identifying the type of event, the same data length bus voltage magnitude and frequency synchronized measurements are utilized to develop statistical measures based novel indices. A rule‐based inference from event's signature is also developed to validate the usefulness of indices for classification and location identification of the event. These extracted statistical indices are applied as input to the Random Forest Classifier to classify and locate the events in real‐time. The proposed approach captures real‐time synchronized data and is adaptive to system topological changes. The proposed comprehensive approach for situational awareness is applied to standard IEEE 39 Bus test system and IEEE 118 Bus test system. The results highlight the performance of the composite method for event identification, classification and location identification with less computational burden and high accuracy.

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A fault classification technique for transmission lines using an improved alienation coefficients technique

Cited by 11 publications

References 28 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

k-NN based fault detection and classification methods for power transmission systems

A new synchronized data‐driven‐based comprehensive approach to enhance real‐time situational awareness of power system

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