A transformer model for winding fault studies

Bastard, P.; Bertrand, Pierre; Meunier, Michel

doi:10.1109/61.296246

Cited by 189 publications

(120 citation statements)

References 1 publication

Supporting

Mentioning

117

Contrasting

Unclassified

Order By: Relevance

“…Various types of internal winding faults, namely, LG, LL, and LLG are applied at 5%, 10%, 25%, 50%, 75%, and 90% from the terminal of the transformer, including terminal faults with a varying fault inception angle (FIA) from 0 to 165 in steps of 15 along with a change in source impedance values. Turn-To-Turn Fault: It has observed from surveys and case studies that 70%-80% of power transformer failures are eventually due to turn-to-turn insulation failures [11].…”

Section: Internal Faultsmentioning

confidence: 99%

Distinguishing the Various Faults in transformer and Its Protection Using Support Vector Machine

athan¹,

ithra²

2015

IJAREEIE

View full text Add to dashboard Cite

This paper presents a new differential protection scheme based on support vector machine (SVM), which delivers effective distinguish between internal faults in a power transformer with the other disturbance, such as overexcitation conditions. In existing method, the internal faults only considered and the linear programming method detects the faults at one set value of the system. In the proposed method, the Support Vector Machine (SVM) is used to detect the various types of faults in the system. An SVM classifier gives identical promising results for CT saturation, different connection type, and various ratings of the transformer, even though it is trained only once for a single rating and connection of a transformer. This scheme provides a fault tripping time is 10 ms. Numerous simulation cases consisting of internal faults and other disturbance have been simulated with varying fault and system parameters for an existing power transformer using the MATLAB/Simulink software package.

show abstract

Section: Internal Faultsmentioning

confidence: 99%

Distinguishing the Various Faults in transformer and Its Protection Using Support Vector Machine

athan¹,

ithra²

2015

IJAREEIE

View full text Add to dashboard Cite

show abstract

“…If a transformer terminal model is known in terms of winding resistance, self and mutual inductances, therefore, 6×6 RL matrices from BCTRAN routine can be formed for a three phase two winding transformer, and also 7×7 and 8×8 matrices can be derived for turn to earth and turn to turn fault studies, respectively [13]- [14]. So, in order to simulate turn to turn and turn to earth faults, the b-phase of primary winding is divided into three parts with 637, 49 and 294 turns, as shown in Fig.2.…”

Section: Simulation Modelsmentioning

confidence: 99%

Application of Discrete S-Transform for Differential Protection of Power Transformers

Ashrafian¹,

Rostami²,

Gharehpetian³

et al. 2012

IJCEE

View full text Add to dashboard Cite

Abstract-In this paper, a novel scheme based on Hyperbolic S-Transform (HST) is proposed for digital differential protection of power transformers. Hyperbolic S-transform is a powerful tool for non-stationary signal analysis in noisy conditions. Decision logic has been devised using extracted feature from differential currents due to transient phenomena in transformers. The HST of the differential current is calculated. Then, a Decision Index (DI) is calculated according to the spectral energy and standard deviation of the S-matrix. It is seen that DI values are different in the cases of internal faults and inrush currents. The scheme has been implemented in MATLAB environment and the inputs are differential currents derived from EMTP software. In order to simulate the internal turn to turn and turn to earth faults, the power transformer is modeled using 8×8 RL matrices obtained from the subroutine BCTRAN of EMTP software. The differential current signals are infected by noise and the robustness of the algorithm under noisy conditions is investigated.

show abstract

“…Equation (14) is subtracted from Equation (16) to derive Equation (19), Equation (15) from Equation (14) to derive Equation (20), and Equation (16) …”

Section: Three-winding Three-phase Y-y-δ Transformermentioning

confidence: 99%

Induced Voltages Ratio-Based Algorithm for Fault Detection, and Faulted Phase and Winding Identification of a Three-Winding Power Transformer

et al. 2014

View full text Add to dashboard Cite

This paper proposes an algorithm for fault detection, faulted phase and winding identification of a three-winding power transformer based on the induced voltages in the electrical power system. The ratio of the induced voltages of the primary-secondary, primary-tertiary and secondary-tertiary windings is the same as the corresponding turns ratio during normal operating conditions, magnetic inrush, and over-excitation. It differs from the turns ratio during an internal fault. For a single phase and a three-phase power transformer with wye-connected windings, the induced voltages of each pair of windings are estimated. For a three-phase power transformer with delta-connected windings, the induced voltage differences are estimated to use the line currents, because the delta winding currents are practically unavailable. Six detectors are suggested for fault detection. An additional three detectors and a rule for faulted phase and winding identification are presented as well. The proposed algorithm can not only detect an internal fault, but also identify the faulted phase and winding of a three-winding power transformer. The various test results with Electromagnetic Transients Program (EMTP)-generated data show that the proposed algorithm successfully discriminates internal faults from normal operating OPEN ACCESSEnergies 2014, 7 6032 conditions including magnetic inrush and over-excitation. This paper concludes by implementing the algorithm into a prototype relay based on a digital signal processor.

show abstract

A transformer model for winding fault studies

Cited by 189 publications

References 1 publication

Distinguishing the Various Faults in transformer and Its Protection Using Support Vector Machine

Distinguishing the Various Faults in transformer and Its Protection Using Support Vector Machine

Application of Discrete S-Transform for Differential Protection of Power Transformers

Induced Voltages Ratio-Based Algorithm for Fault Detection, and Faulted Phase and Winding Identification of a Three-Winding Power Transformer

Contact Info

Product

Resources

About