Wavelet-Based and Database Approach for Locating Faulty Section of High Impedance Fault in a Distribution System

• Autorzy: Ali M. S. , Bakar A. H. A. , Mokhlis H. , Arof H. , Illias H. A.

Warianty tytułu

PL

Lokalizacja awaryjnej sekcji w przypadku awarii izolatora w sieci dystrybucji energii elektrycznej – wykorzystanie analizy danych i transformacji falkowej

• Języki publikacji: EN

Abstrakty

EN

Locating a faulty section of the high impedance fault (HIF) in a power system network is a major challenge especially for a distribution network. This is due to the effect of the complexity of the distribution network such as branches, non-homogenous lines and high fault impedance that results in variation of fault locations. In this paper, analysis of fault locations using Discrete Wavelet Transform-based Multi-Resolution Analysis (MRA) has been proposed. A three-phase voltage signal measured at the main substation is analyzed to locate the high impedance fault. The 1st, 2nd and 3rd levels of detailed coefficient resolution for each phase were used for the classification of fault locations using the proposed method. The simulation was conducted on a 38-node distribution network system in a national grid in Malaysia using PSCAD software. The proposed method has successfully determined the actual fault location of a high impedance fault.

PL

W artykule przedstawiono analizę metody lokalizacji awarii w sieci energetycznej, wykorzystującej analizę wielo-wynikową (ang. Multiresolution Analysis), opartą na dyskretnej transformacji falkowej. Analizie poddawany jest sygnał pomiarowy napięcia trójfazowego w podstacji. Przeprowadzono badania symulacyjne w programie PSCAD na systemie dystrybucji energii elektrycznej o 38 korzeniach w malezyjskich państwowych sieciach energetycznych.

Słowa kluczowe

EN

faulty section; high Impedance fault; multiresolution analysis

PL

MRA; dyskretna transformata falkowa; lokalizacja awarii

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2013
• Tom: R. 89, nr 1a
• Strony: 211--218
• Opis fizyczny: Bibliogr. 23 poz., rys., schem., tab., wykr.

Twórcy

autor

Ali M. S.

• Department of Electrical Engineering, Faculty of Engineering, University of Malaya

autor

Bakar A. H. A.

• UM Power Energy Dedicated Advanced Centre (UMPEDAC), Level 4, Wisma R&D University of Malaya, Jalan Pantai Baharu, 59990 Kuala Lumpur

autor

Mokhlis H.

• Department of Electrical Engineering, Faculty of Engineering, University of Malaya
• UM Power Energy Dedicated Advanced Centre (UMPEDAC), Level 4, Wisma R&D University of Malaya, Jalan Pantai Baharu, 59990 Kuala Lumpur

autor

Arof H.

• Department of Electrical Engineering, Faculty of Engineering, University of Malaya

autor

Illias H. A.

• Department of Electrical Engineering, Faculty of Engineering, University of Malaya
• UM Power Energy Dedicated Advanced Centre (UMPEDAC), Level 4, Wisma R&D University of Malaya, Jalan Pantai Baharu, 59990 Kuala Lumpur

Bibliografia

• [1] Kejun Mei, S.M. Rovnyak, Chee-Mun Ong, Dynamic Event Detection using Wavelet Analysis, Power Engineering Society General Meeting, IEEE, 2006,pp.7.
• [2] S. Bruno, M. De Benedictis, M. La Scala, Emergency Control Assessment for Mitigating the Effects of Cascading Outages, CIGRE 2006. http://www.cigre.org/
• [3] M. Bronzini, S. Bruno, M. De Benedictis, M. La Scala, Power System Modal Identification via Wavelet Analysis, IEEE Lausanne Power Tech, 2007, pp. 2041-2046.
• [4] S. Avdakovic, A. Nuhanovic, Identifications and Monitoring of Power System Dynamics Based on the PMUs and Wavelet Technique, Engineering and Technology, 2010, pp. 796-803.
• [5] S. Avdakovic, A. Nuhanovic, M. Kusljugic, M. Music, Wavelet Transform Applications in Power System Dynamics,” Electric Power Systems Research, 2010.
• [6] W. Gao, J. Ning, Wavelet-Based Disturbance Analysis for Power System Wide-Area Monitoring, IEEE Transactions on Smart Grid, vol. 2, n. 1, 2011, pp. 121-130.
• [7] T. M. Lai, L. A. Snider, E. Lo, D. Sutanto, High-Impedance Fault Detection using Discrete Wavelet Transform and Frequency Range and RMS Conversion, IEEE Transactions on Power Delivery, vol. 20, n. 1, 2005, pp. 397-407.
• [8] A. H. Etemadi, M. Sanaye-Pasand, High-impedance Fault Detection using Multi-resolution Signal Decomposition and Adaptive Neural Fuzzy Inference System, IET Generation, Transmission & Distribution, vol. 2, n. 1, 2008, p. 110.
• [9] M. Michalik, M. Lukowicz, W. Rebizant, S.-J. Lee, S.-H. Kang, Verification of the Wavelet-Based HIF Detecting Algorithm Performance in Solidly Grounded MV Networks, IEEE Transactions on Power Delivery, vol. 22, n. 4, 2007, pp. 2057- 2064.
• [10] M. Sarlak, S. M. Shahrtash, High Impedance Fault Detection using Combination of Multi-layer Perceptron Neural Networks Based on Multi-resolution Morphological Gradient Features of Current Waveform, IET Generation, Transmission & Distribution, vol. 5, n. 5, 2011, p. 588.
• [11] M. Mirzaei, M. Z. A. A. Kadir, E. Moazami, H. Hizam, Review of Fault Location Methods for Distribution Power System, Australian Journal of Basic and Applied Sciences vol. 3, n. 3, 2009, pp. 2670-2676.
• [12] T. Short, J. Kim, C. Melhorn, Update on Distribution System Fault Location Technologies and Effectiveness, 20th International Conference and Exhibition on Electricity Distribution - Part 1, pp. 1-4, 2009.
• [13] J. Mora, J. Meléndez, M. Vinyoles, J. Sánchez, M. Castro, An Overview to Fault Location Methods in Distribution System Based on Single End Measures of Voltage and Current, ICREPQ’04 – International Conference on Renewable Energy and Power Quality, 2004.
• [14] N. I. Elkalashy, M. Lehtonen, H. A. Darwish, A.-M. I. Taalab, M. A. Izzularab, A Novel Selectivity Technique for High Impedance Arcing Fault Detection in Compensated MV Networks, European Transactions on Electrical Power, vol. 18, n. 4, 2008, pp. 344-363.
• [15] N. I. Elkalashy, M. Lehtonen, H. A. Darwish, A.-M. I. Taalab, M. A. Izzularab, DWT-based Extraction of Residual Currents Throughout Unearthed MV Networks for Detecting Highimpedance Faults Due to Leaning Trees, European Transactions on Electrical Power, vol. 17, n. 6, 2007, pp. 597- 614.
• [16] U. D. Dwivedi, S. N. Singh, S. C. Srivastava, A Wavelet Based Approach for Classification and Location of Faults in Distribution Systems, Annual IEEE India Conference, pp. 488- 493, 2008.
• [17] L. Garcia-Santander, P. Bastard, M. Petit, I. Gal, E. Lopez, H. Opazo, Down-conductor Fault Detection and Location Via a Voltage Based Method For Radial Distribution Networks, IEE Proceedings - Generation, Transmission and Distribution, vol. 152, n. 2, 2005, p. 180.
• [18] Z.-Y. Li, W.-l. Wu, Classification of Power Quality Combined Disturbances Based on Phase Space Reconstruction and Support Vector Machines, Journal of Zhejiang University - Science A, vol. 9, 2008, pp. 173-181.
• [19] S. Chen, Feature Selection For Identification and Classification of Power Quality Disturbances, Power Engineering Society General Meeting, Vol. 3, 2005, pp. 2301-2306.
• [20] P. K. Dash, B. K. Panigrahi, G. Panda, Power Quality Analysis using S-transform, IEEE Transactions on Power Delivery, vol. 18, 2003, pp. 406-411.
• [21] T. K. Abdel-Galil, E. F. El-Saadany, A. M. Youssef, M. M. A. Salama, Disturbance Classification using Hidden Markov Models and Vector Quantization, IEEE Transactions on Power Delivery, vol. 20, 2005, pp. 2129-2135.
• [22] S. Suja, J. Jerome, Pattern Recognition of Power Signal Disturbances using S-Transform and TT-Transform, International Journal of Electrical Power & Energy Systems, vol. 32, 2010, pp. 37-53.
• [23] H. Mokhlis, Hasmaini Mohamad, A.H.A Bakar, H.Y.Li, Evaluation of Fault Location based on Voltage Sags Profiles: a Study on the Influence of Voltage Sags Patterns, International Review of Electrical Engineering (IREE),vol. 6, n.2, March-April 2011 , pg 874-880.