Atributos Relevantes para el Diagnóstico Automático de Eventos de Tensión en Redes de Distribución de Energía Eléctrica

Víctor Barrera Núñez, Ronald Velandia, Fredy Hernández, Joaquim Meléndez, Hermann Vargas

Resumen

En este trabajo se aborda el diagnóstico de eventos o perturbaciones de tensión registradas en subestaciones de distribución. La aparición de dichos eventos se debe a causas diversas que van desde faltas en la red, el arranque de motores de inducción, energización de transformadores y conmutación de bancos de capacitores. Se propone la caracterización de estos eventos de tensión a partir de atributos extraídos directamente de la forma de onda, y que se relacionan con los fenómenos físicos asociados tanto con las causas de los eventos, como con su localización relativa respecto del punto de medida. Se ha estudiado la relevancia de dichos atributos mediante un análisis estadístico de la varianza (MANOVA). Los atributos más relevantes se han utilizado para la obtención de reglas de clasificación mediante algoritmos de aprendizaje automático. Los resultados fueron obtenidos empleando datos de 484 eventos reales y 38 eventos simulados.

Palabras clave

Análisis estadístico; Calidad de la potencia eléctrica; Atributos; Eventos de tensión; Sistema basado en reglas

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Referencias

Barrera V., Berjaga X., Melendez J., Herraiz S., (2008). Two new methods for voltage sag source location. 13th International Conference on Harmonics & Quality of Power, 28 de Septiembre a 1 de Octubre, Australia.

Barrera V., Meléndez J., Herraiz S. (2009). Evaluation of Fault relative location algorithms using voltage sag data collected at 25-kv substations. European Transactions on Electrical Power, 20, 34-51.

Barrera V., Meléndez J., Kulkarni S., Santoso S. (2010) Feature analysis and automatic classification of short-circuit faults resulting from external causes. European Transactions on Electrical Power, DOI: 10.1002/etep.674, January 2012.

Barrera V., Bollen, M., Yu-Hua Gu I., Meléndez, J. (2010). Feature characterization of power quality events according to their underlying causes. 14th International Conference on Harmonics & Quality of Power, 26-29 de Septiembre, Italy.

Barrera V., Kulkarni S., Santoso S., Meléndez J. (2010) SVM-Based classification methodology for overhead distribution fault events. 14th International Conference on Harmonics & Quality of Power, 26-29 de Septiembre, Italy.

Barrera V., Kulkarni S., Santoso S., Melendez J. (2010) Feature analysis and classification methodology for overhead distribution fault events. IEEE Power & Energy Society, 2010 General Meeting. 25-29 de Julio, USA.

Blanco J., Jagua J., Barrera. V, Jaimes, L. (2009) Metodología para el diagnóstico de la causa de huecos de tensión: análisis de fallas, Tesis de grado, Publicaciones UIS, http://tangara.uis.edu.co/biblioweb/tesis/2009/132235.PDFColombia.

Bollen M. (2000) Understanding Power Quality Problems: Voltages Sags and Interruptions, IEEE PRESS, New York. Bollen M. (2003) Algorithms for characterizing measured three-phase unbalanced voltage dips. IEEE Transactions on Power Delivery, 18, 937 - 944.

Bollen, M., Yu-Hua, I. Axelberg, P., Styvaktakis, E. (2007) Classification of underlying causes of power quality disturbances: Deterministic versus Statistical methods. EURASIP Journal on Advances in Signal Processing. 2007, 1-17.

Clark P, Niblett T. (1989) The CN2 induction algorithm. Machine Learning Journal, 3/4: 261-283.

Clark P and R. Boswell. (1991) Rule induction with CN2: Some recent improvements. In Y. Kodratoff, editor, Machine Learning - EWSL-91, Springer-Verlag: Berlin, 151-163.

Coury, D.V., Tavarez C.J. (1998) Transient analysis resulting from shunt capacitor switching in an actual electrical distribution system, 8th International Conference on Harmonics & Quality of Power, Athens.

Grid 2030 - A National Vision for Electricity’s Second 100 Years (2003), United States Department of Energy.

Hamzah N., Mohamed A., Hussain A. (2005) Locating voltage sag source at the point of common coupling in industrial distribution systems. IEEE International Conference on Power Electronics and Drive Systems. 28-1 de Noviembre, Malasia.

Hernández, J, Quintana, M.J, Ramírez, C. (2004) Introducción a la minería de datos. Pearson Prentice Hall, Addison-Wesley.

Ibrahim, W., Morcos M. (2002) “Artificial Intelligence and Advanced Mathematical Tools for Power Quality Aplications: A Survey”, IEEE Transactions on Power Delivery, 17, 668.

Kersting, W. H. (2000) Radial distribution test feeders. Power engineering Society, USA.

Kulkarni S., Lee D., Allen A., Santoso S., Short T., (2010) Waveform Characterization of Animal Contact, Tree Contact, and Lightning Induced Faults, IEEE Power & Energy Society, 2010 General Meeting. 25-29 de Julio, USA.

McGranaghan M, B. Roettger. (2002) “Economic evaluation of power quality”. IEEE Power Engineering Review, 22 (2), 8-12.

McGranahan M. (2001) “Trends in Power Quality Monitoring”, IEEE Power Engineering Review.

Pradhan A.K, Routray A., Madhan S. (2007). Fault direction estimation in radial distribution system using phase change in sequence current. IEEE Transactions on Power Delivery, 22, 2065-2071.

Seon A., Dong W., Li C., Seung M. (2004) “Determination of the Relative Location of Voltage sag source According to event Cause”, Power Engineering Society General Meeting, 1, 620 - 625.

Styvaktakis E., (2002) Automating power quality analysis, Ph.D. thesis, Chalmers University of Technology, Sweden, 2002.

Tayjasanant T., C. Li, and W. Xu. (2005) A resistance sign-based method for voltage sag source detection. IEEE Transactions on Power Delivery, 20, 2544-51, 2005.

Velandia R., Hernández F., Barrera, V., Vargas, H. (2010) Evaluación de algoritmos de extracción de reglas de decisión para el diagnóstico de huecos de tensión, Tesis de grado, Publicaciones Universidad Industrial de Santander, Colombia.

Xu L, Mo-Yuen C. (2006) A classification approach for power distribution systems fault cause identification, IEEE Transaction on Power System; 21, 53-60.

Xu L, Chow M, Taylor L. (2007) Power Distribution Fault Cause Identification With Imbalanced Data Using the Data Mining-Based Fuzzy Classification E-Algorithm. IEEE Transaction on Power Systems, 22, 164-171.

Yalcinkaya G., Bollen MHJ., Crossley P.A. (1998) Characterization of voltage sags in industrial distribution Systems. IEEE Transactions on Industry Applications, 34, 682-688.

Yixin C, Mo-Yuen C, Wenbin L, Lexin L. (2010) Evaluation of distribution fault diagnosis algorithms using ROC curves, 25 a 29 de Julio, USA.

Yixin C, Mo-Yuen C, Wenbin L, Lexin L. Statistical Feature Selection From Massive Data in Distribution Fault Diagnosis. IEEE Transaction on Power Systems 2010: 25 (2), 642-648.

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Integrated Computer-Aided Engineering  vol: 25  num.: 4  primera página: 397  año: 2018  
doi: 10.3233/ICA-180576



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Universitat Politècnica de València     https://doi.org/10.4995/riai

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