A modular methodology for fast fault detection and classification in power systems

Chowdhury, Fahmida; Aravena, J.L.

doi:10.1109/87.709497

Cited by 49 publications

(18 citation statements)

References 17 publications

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“…The existing solutions can be classified in two different categories [Chowdhury, 1998;Isermann 2004]: a) Fault detection and identification using dedicated observers, detection and identification algorithms, and smart AHS simulation. b) Fault management using FDIM architecture and simulation results.…”

Section: Fault Detection and Isolation Structurementioning

confidence: 99%

Fault Detection of Actuators in Superheaters Temperature Control Systems

Vînătoru

Iancu

2005

IFAC Proceedings Volumes

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Section: Fault Detection and Isolation Structurementioning

confidence: 99%

Fault Detection of Actuators in Superheaters Temperature Control Systems

Vînătoru

Iancu

2005

IFAC Proceedings Volumes

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“…The benefits of applying wavelet transform in fault location of power system have already been recognized by many researchers [5][6][7][8][9][10][11][12]. However, the wavelet transform itself has limitations for accurate fault location because there are many irregular waveforms in measured original signal.…”

Section: Introductionmentioning

confidence: 99%

Development of Fault Location Algorithm and Its Verification Experiments for HVDC Submarine Cables

Jung¹,

Park²,

Kang³

et al. 2012

Journal of Electrical Engineering and Technology

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-A new fault location algorithm based on stationary wavelet transform and its verification experiment results are described for HVDC submarine cables in this paper. For wavelet based fault location algorithm, firstly, 4th level approximation coefficients decomposed by wavelet transform function are superimposed by correlation, then the distance to the fault point is calculated by time delay between the first incident signal and the second reflected signal. For the verification of this algorithm, the real experiments based on various fault conditions and return types of fault current are performed at HVDC submarine cable test yard located in KEPCO(Korea Electric Power Corporation) Power Testing Center of South Korea. It proves that the fault location method proposed in this paper is very simple but very quick and accurate for HVDC submarine cable fault location.

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“…Diverse protecting mechanisms of transmission lines have been proposed earlier to detect and classify fault utilizing high frequency noise generated by fault and NNs [5], initial current travelling wave technique [6], wavelet transform [7], wavelet fuzzy combined approach [8], high speed protective relaying using ANN architecture and digital signal processing concepts. [9], modular yet integrated approach using modified Kohonen-type neural network [10], combined supervised and unsupervised neural network with ISODATA clustering algorithm [11], RBF NN with OLS learning method [12] and Combined fuzzy neural network [13][14][15][16] wavelet analysis and ANN [17][18][19], ANN Approach [20][21][22][23][24][25]. However these techniques did not identify the fault direction and section.…”

Section: Introductionmentioning

confidence: 99%

ANN based directional relaying scheme for protection of Korba-Bhilai transmission line of Chhattisgarh state

Yadav

Dash

Ashok

2016

Prot Control Mod Power Syst

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As it is crucial to protect the transmission line from inevitable faults consequences, intelligent scheme must be employed for immediate fault detection and classification. The application of Artificial Neural Network (ANN) to detect the fault, identify it's section, and classify the fault on transmission lines with improved zone reach setting is presented in this article. The fundamental voltage and current magnitudes obtained through Discrete Fourier Transform (DFT) are specified as the inputs to the ANN. The relay is placed at section-2 which is the prime section to be protected. The ANN was trained and tested using diverse fault datasets; obtained from the simulation of different fault scenarios like different types of fault at varying fault inception angles, fault locations and fault resistances in a 400 kV, 216 km power transmission network of CSEB between Korba-Bhilai of Chhattisgarh state using MATLAB. The simulation outcomes illustrated that the entire shunt faults including forward and reverse fault, it's section and phase can be accurately identified within a half cycle time. The advantage of this scheme is to provide a major protection up to 99.5% of total line length using single end data and furthermore backup protection to the forward and reverse line sections. This routine protection system is properly discriminatory, rapid, robust, enormously reliable and incredibly responsive to isolate targeted fault.

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A modular methodology for fast fault detection and classification in power systems

Cited by 49 publications

References 17 publications

Fault Detection of Actuators in Superheaters Temperature Control Systems

Fault Detection of Actuators in Superheaters Temperature Control Systems

Development of Fault Location Algorithm and Its Verification Experiments for HVDC Submarine Cables

ANN based directional relaying scheme for protection of Korba-Bhilai transmission line of Chhattisgarh state

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