High impedance arcing fault detector for three-wire power distribution networks
ABSTRACT A new approach to a high impedance fault (HIF) detector is presented, suitable for the European scene where the power distribution systems are usually three-phase and three-wire configured. This paper aims to be a contribution to the proposals that, in the last twenty years, have been trying to solve the HIF problem with no definitive solution known yet. The purpose of the study presented is to design an electric arc detector and characterise the danger of the fault looking at fault context conditions. The detector system input signals are the three individual phase currents which comply with 3I0=I1+I2+I3≠0 at the three-wire configuration. First, a continuous HIF context conditions study is proposed: overcurrent or reclosing in every phase, noticeable load variation monitoring and 3I0 monitoring. Secondly, a short, medium and long-term statistical analysis is performed both with odd harmonics (third, fifth, seventh and ninth) and even harmonics (second and fourth) of the I0 current. Thirdly, the estimated arc probability is calculated and combined with context conditions in order to determine a diagnosis. The proposed detector has been tested on 100 unfaulted condition event records (some have leakage current) and 32 staged fault records on different surfaces. The test results presented in the paper are satisfactory both in the sense of dependability and sensitivity.
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ABSTRACT: High-impedance faults (HIFs) on distribution system still present the most persistent and challenging problem to protection engineers due to the fact that HIFs do not produce enough fault current, thus not detectable by conventional over-current protection devices. Previous research shows that it is possible to distinguish HIFs from other similar waveforms such as nonlinear load currents by analyzing the harmonic contents. A method for HIF detection based on the harmonic analysis of current waveforms is presented here. A harmonic detection program is implemented in MATLAB using both Interpolation Windowed Fast Fourier Transform and All-phase Fast Fourier Transform algorithms. Various simulation results and real-world data analysis show that this harmonic detection program can accurately, reliably and quickly determine the harmonic contents (including frequency, amplitude and phase angle of each harmonic) in an arbitrary signal without knowing its mathematical expression. Simulation results also show that this harmonic detection program could be used for feature extraction and pattern recognition for HIF detection in the future.IPEC, 2012 Conference on Power & EnergyIPEC, 2012 Conference on Power & Energy; 01/2012
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ABSTRACT: Bridging the gap between the theoretical modeling and the practical implementation is always essential for fault detection, classification, and location methods in a power transmission-line network. In this paper, a novel hybrid framework that is able to rapidly detect and locate a fault on power transmission lines is presented. The proposed algorithm presents a fault discrimination method based on the three-phase current and voltage waveforms measured when fault events occur in the power transmission-line network. Negative-sequence components of the three-phase current and voltage quantities are applied to achieve fast online fault detection. Subsequently, the fault detection method triggers the fault classification and fault-location methods to become active. A variety of methods-including multilevel wavelet transform, principal component analysis, support vector machines, and adaptive structure neural networks-are incorporated into the framework to identify fault type and location at the same time. This paper lays out the fundamental concept of the proposed framework and introduces the methodology of the analytical techniques, a pattern-recognition approach via neural networks and a joint decision-making mechanism. Using a well-trained framework, the tasks of fault detection, classification, and location are accomplished in 1.28 cycles, significantly shorter than the critical fault clearing time.IEEE Transactions on Power Delivery 08/2011; · 1.52 Impact Factor
Conference Paper: Detection of Electrical Arc Faults in a Distribution Network[Show abstract] [Hide abstract]
ABSTRACT: In this paper, a new method for the detection of electrical arc faults is presented It is possible, by using a digital signal processor programmed with Matlab/Simulink, to create a system able to detect the presence of unwanted frequencies in the distribution network. Those frequencies are often generated by an electrical arc in the network.Electrical and Computer Engineering, 2007. CCECE 2007. Canadian Conference on; 05/2007