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Proceedings ArticleDOI

An EMD Based Protection Scheme for Distribution System

01 Oct 2018-Vol. 2018, pp 17-22
TL;DR: A protection scheme which makes use of Empirical Mode Decomposition of three phase current signals of a distribution network and establishes selectivity by testing the algorithm with non faulty transients such as load switching and capacitor switching.
Abstract: Fast identification and classification of the faults in distribution network is a crucial task to ensure reliable power supply to the end user. This paper presents a protection scheme which makes use of Empirical Mode Decomposition of three phase current signals of a distribution network. The current signals measured at the substation bus over a moving window of one cycle are decomposed to obtain first level intrinsic mode function IMF 1 and residue R 1 . A fault index which is nothing but the absolute mean of R 1 is calculated for each phase and compared with a threshold to detect and categorize the type of fault. The proposed algorithm has been successfully tested on IEEE 13 bus system by varying the type of fault, fault incidence angle and fault location. The selectivity of the proposed scheme has been established by testing the algorithm with non faulty transients such as load switching and capacitor switching.
Citations
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Proceedings ArticleDOI
27 Jul 2014
TL;DR: In this paper, the authors developed a method based on combination of empirical mode decomposition (EMD) and Hilbert transform for assessment of power quality events, which can be conceived as superimposition of various oscillating modes and EMD is used to separate out these intrinsic modes known as intrinsic mode functions (IMF).
Abstract: The aim of this paper is to develop a method based on combination of Empirical Mode Decomposition (EMD) and Hilbert Transform for assessment of power quality events. A distorted waveform can be conceived as superimposition of various oscillating modes and EMD is used to separate out these intrinsic modes known as intrinsic mode functions (IMF). Hilbert transform is applied to first three IMF to obtain instantaneous amplitude and phase which are then used for constructing feature vector. The work evaluates the detection capability of the methodology and a comparison with S-Transform is made to show the superiority of the technique in detecting the PQ disturbance like voltage spike and notch. A Probabilistic Neural Network is used as a mapping function for identifying the various disturbance classes. Results show a better classification accuracy of the methodology.

40 citations

Journal ArticleDOI
TL;DR: The proposed fault identification technique makes use of the empirical mode decomposition of three-phase current signals of a distribution network to detect, classifying, and locating faults with DG penetration in the presence of noise within half cycle.
Abstract: This article presents a fault identification technique that makes use of the empirical mode decomposition of three-phase current signals of a distribution network. The current signals measured at the substation bus over a moving window are decomposed to obtain the first-level intrinsic mode function and residue. The standard deviation of the first-level residue is calculated as a fault index for each phase and compared with a threshold to detect and categorize the type of fault. A ground fault index based on the average value of the first-level residue of the neutral current is proposed to discriminate the phase–phase and phase–phase–ground faults. The proposed algorithm has been successfully tested on the IEEE 13 bus and 34 bus distribution systems in the presence of the solar photovoltaic power plant by varying the type of fault, fault incidence angle, and fault location in the presence of noise. The selectivity of the proposed algorithm has been established by testing the algorithm with nonfaulty transients such as transformer excitation and deexcitation, feeder energization and deenergization, load switching, capacitor switching, and also those associated with distributed generation (DG) penetration like islanding and tripping of DG. Subsequently, the residue-based features are fed to a decision tree to locate the faults on the distribution system. Thus, the proposed algorithm has been successful in detecting, classifying, and locating faults with DG penetration in the presence of noise within half cycle by utilizing only current signals.

13 citations


Cites background from "An EMD Based Protection Scheme for ..."

  • ...these unpredictable faults have to be identified as quickly as possible [1]....

    [...]

Journal ArticleDOI
TL;DR: A fast protection algorithm based on Hilbert-Huang transform (HHT) is proposed in this article for islanding and fault detection, classification, and location in a distribution system penetrated by a solar renewable energy source.

9 citations

References
More filters
Journal ArticleDOI
TL;DR: In this article, an intelligent approach for high impedance fault detection in power distribution feeders using combined Adaptive Extended Kalman Filter (AEKF) and probabilistic neural network (PNN) is presented.

65 citations


"An EMD Based Protection Scheme for ..." refers methods in this paper

  • ...Kalman filtering theory [1], S-Trasform [3][4], Wavelet Transform [5]- [6], Gabor Wigner transform [7] are employed in extracting the frequency information with respect to time....

    [...]

Proceedings ArticleDOI
27 Jul 2014
TL;DR: In this paper, the authors developed a method based on combination of empirical mode decomposition (EMD) and Hilbert transform for assessment of power quality events, which can be conceived as superimposition of various oscillating modes and EMD is used to separate out these intrinsic modes known as intrinsic mode functions (IMF).
Abstract: The aim of this paper is to develop a method based on combination of Empirical Mode Decomposition (EMD) and Hilbert Transform for assessment of power quality events. A distorted waveform can be conceived as superimposition of various oscillating modes and EMD is used to separate out these intrinsic modes known as intrinsic mode functions (IMF). Hilbert transform is applied to first three IMF to obtain instantaneous amplitude and phase which are then used for constructing feature vector. The work evaluates the detection capability of the methodology and a comparison with S-Transform is made to show the superiority of the technique in detecting the PQ disturbance like voltage spike and notch. A Probabilistic Neural Network is used as a mapping function for identifying the various disturbance classes. Results show a better classification accuracy of the methodology.

40 citations

Journal ArticleDOI
TL;DR: Two short circuit techniques, the symmetrical components and phase components algorithms are implemented and analyzed based on numerical simulations of the IEEE 13 bus test feeder, showing that the during-fault voltages and currents are greatly affected by both voltage unbalance and fault impedance.
Abstract: This paper presents a numerical study of the system unbalance and the fault impedance effect on faulted power system analysis. Two short circuit techniques, the symmetrical components and phase components algorithms are implemented and analyzed based on numerical simulations of the IEEE 13 bus test feeder. Test cases include voltage unbalance effect and fault impedance effect on during-fault voltages and currents. The results show that the during-fault voltages and currents are greatly affected by both voltage unbalance and fault impedance.

35 citations


"An EMD Based Protection Scheme for ..." refers methods in this paper

  • ...Power quality events are detected using first three IMFs which contain high frequency content in [10]....

    [...]

Proceedings ArticleDOI
01 Oct 2015
TL;DR: In this paper, a novel S-transform based approach to detect high impedance fault in distribution line is presented, where features extracted using S-Transform are used to train and test the ANN to discriminate the HIF with other transient phenomenon (Load switching, capacitor Switching) and also normal fault and no fault condition.
Abstract: This paper presents a novel S-transform based approach to detect High impedance fault in distribution line. Conventional Distance relays , over current relays and ground fault relays are difficult to apply for High Impedance Fault (HIF) detection in distribution line because of sensitivity, diversity, selectivity issue in case of low value of fault current. As S-Transform (ST) is a very useful tool to analyzing transient fault signal which also provide both time and frequency information unlike Fourier transform, same has been consider for High impedance fault detection. The Features extracted using S-Transform are used to train and test the Artificial Neural Network (ANN) to discriminate the HIF with other transient phenomenon (Load switching, capacitor Switching) and also normal fault and no fault condition. The proposed scheme are fully analyzed with different operating condition by extensive MATLAB simulation studies that clearly revels that the proposed method can detect High impedance Faults in high voltage distribution line with high accuracy)

34 citations


"An EMD Based Protection Scheme for ..." refers methods in this paper

  • ...Kalman filtering theory [1], S-Trasform [3][4], Wavelet Transform [5]- [6], Gabor Wigner transform [7] are employed in extracting the frequency information with respect to time....

    [...]

Journal ArticleDOI
TL;DR: In this paper, the Hilbert-Huang transform (HHHT) was used to decompose all lines connecting to the busbar into intrinsic-mode functions and calculate the instantaneous amplitude of the first intrinsic mode function (IMF).
Abstract: A new algorithm for busbar protection is proposed based on the Hilbert–Huang transform in this study. The algorithm decomposes currents of all lines connecting to the busbar into intrinsic-mode functions and calculates the instantaneous amplitude of the first intrinsic mode function (IMF). Then, the instantaneous amplitude is normalised to eliminate the impact of fault initial angle and transition resistance. When a fault occurs on the busbar, the initial travelling waves on head ends of the lines all have great instantaneous amplitudes; when a fault occurs on any line, the travelling wave on the faulted line is of great instantaneous amplitude, whereas the initial travelling waves on healthy lines are of small instantaneous amplitudes. Thus, through analysing the detected instantaneous amplitudes of travelling waves, a new busbar protection scheme can be constructed, which achieves a high reliability relative to other fault-travel-wave-based algorithms. According to simulation results on a 500 kV substation modelled in ATP-Draw, the graphical preprocessor to ATP-EMTP windows version, the proposed algorithm is effective in determining various types of faults.

30 citations