Grid-connected induction generator interturn fault analysis using a PCA-ANN based algorithm

is difficult for short circuits among the internal windings of one phase in electrical machines to be determined in a reliable and speedy manner. The failure currents that occur, especially in short circuits with a few windings, are at such low levels that they cannot be determined by relay systems. This results in growing faults and damage. In this study, we designed a model that can define winding failures successfully at very small levels by using the PCA and ANN algorithms. We tested the real-time faults and measured the system performance with the installed test rig. The developed protection model determined fault determination in very small (2.5%) winding failures with acceptable accuracy. The suggested model is a counter-speed, selective, flexible, and economical protection model that may be used for internal failures of electrical machines. It has a structure that may be used in different systems or kinds of failure with data receiving and software changes.

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[1] Rushton J, Mewes KGM. Protection of generators, transformers, generator-transformer units and transformer feeders. In: The Electricity Training Association, editor. Power System Protection 3. London, UK: Short Run Press Ltd, 1995.
[2] S¨urgevil T, Akpınar E. Modelling of a 5 kW wind energy conversion system with induction generator and comparison with experimental results. Renew Energ 2005; 30: 913-929.
[3] Freitas W, Vieira JCM, Morelato A, da Silva LCP, da Costa VF, Lemos FAB. Comparative analysis between synchronous and induction machines for distributed generation applications. IEEE T Power Syst 2006; 21: 301-311.
[4] Quinonez-Varela G, Cruden A. Modelling and validation of a squirrel cage induction generator wind turbine during connection to the local grid. IET Gener Transm Dis 2008; 2: 301-309.
[5] Holdsworth L, Wu XG, Ekanayake JB, Jenkins N. Comparison of fixed speed and doubly-fed induction wind turbines during power system disturbances. IEE P-Gener Transm D 2003; 150: 343-352.
[6] Abad G, Rodriguez MA, Iwanski G, Poza J. Direct power control of doubly fed induction generator based wind turbines under unbalanced grid voltage. IEEE T Power Electr 2010; 25: 442-452.
[7] Lopez J, Gubia E, Olea E, Ruiz J, Marroyo L. Ride through of wind turbines with doubly fed induction generator under symmetrical voltage dips. IEEE T Ind Electron 2009; 56: 4246-4254.
[8] Flannery PS, Venkataramanan G. A fault tolerant doubly fed induction generator wind turbine using a parallel grid side rectifier and series grid side converter. IEEE T Power Electr 2008; 23: 1126-1135.
[9] Chen SZ, Cheung NC, Wong KC, Wu J. Grid synchronization of doubly fed induction generator using integral variable structure control. IEEE T Energy Conver 2009; 24: 875-883.
[10] Xiang D, Ran L, Tavner PJ, Yang S. Control of a doubly fed induction generator in a wind turbine during grid fault ride-through. IEEE T Energy Conver 2006; 21: 652-662.
[11] Zhang J, Dysko A, OReilly J, Leithead WE. Modelling and performance of fixed-speed induction generators in power system oscillation stability studies. Electr Pow Syst Res 2008; 78: 1416-1424.
[12] Wamkeue R, Kamwa I. Generalized modeling and unbalanced fault simulation of saturated self-excited induction generators. Electr Pow Syst Res 2002; 61: 11-21.
[13] Wekhande S, Agarwal V. A new variable speed constant voltage controller for self-excited induction generator. Electr Pow Syst Res 2001; 59: 157-164.
[14] Idjdarene K, Rekioua D, Rekioua T, Tounzi A. Vector control of autonomous induction generator taking saturation effect into account. Energ Convers Manage 2008; 49: 2609-2617.
[15] Joshi D, Sandhu KS, Soni, MK. Constant voltage constant frequency operation for a self-excited induction generator. IEEE T Energy Conver 2006; 21: 228-234.
[16] Jain SK, Sharma JD, Singh SP. Transient performance of three-phase self-excited induction generator during balanced and unbalanced faults. IEE Proc-C 2002; 149: 50-57.
[17] Boutsika TN, Papathanassiou SA. Short-circuit calculations in networks with distributed generation. Electr Pow Syst Res 2008; 78: 1181-1191.
[18] Widodo A, Yang B, Gu D, Cho B. Intelligent fault diagnosis system of induction motor based on transient current signal. Mechatronics 2009; 19: 680-689.
[19] Ghate VN, Dudul SV. Optimal MLP neural network classifier for fault detection of three phase induction motor. Expert Syst Appl 2010; 37: 3468-3481.
[20] Combastel, C, Lesecq S, Petropol S, Gentil S. Model-based and wavelet approaches to induction motor on-line fault detection. Control Eng Pract 2002; 10: 493-509.
[21] He Y, Tan Y, Sun Y. Wavelet neural network approach for fault diagnosis of analogue circuits. IEE Proc-G 2004; 151: 379-384.
[22] Gketsis ZE, Zervakis ME, Stavrakakis G. Detection and classification of winding faults in windmill generators using wavelet transform and ANN. Electr Pow Syst Res 2009; 79: 1483-1494.
[23] Acosta GG, Verucchi CJ, Gelso ER. A current monitoring system for diagnosing electrical failures in induction motors. Mech Syst Signal Pr 2006; 20: 953-965.
[24] Martins JF, Pires VF, Pires AJ. PCA-Based on-line diagnosis of induction motor stator fault feed by PWM inverter. In: IEEE 2006 International Symposium on Industrial Electronics; 9-12 July 2006; Montreal, Quebec, Canada: IEEE. pp. 2401-2405.
[25] Shah D, Nandi S, Neti P. Stator interturn fault detection of doubly fed induction generators using rotor-current and search-coil-voltage signature analysis. IEEE T Ind Appl 2009; 45: 1831-1842.
[26] Emhemed AS, Tumilty RM, Singh NK, Burt GM, McDonald JR. Analysis of transient stability enhancement of lv-connected induction microgenerators by using resistive-type fault current limiters. IEEE T Power Syst 2010; 25: 885-893.
[27] Kılı¸c E, Ozg¨onenel O, Usta ¨ O, Thomas D. PCA based protection algorithm for transformer internal faults. Turk J ¨ Electr Eng & Com Sci 2009; 17: 125-142.
[28] Ozgonenel O, Yalcin T. A complete motor protection algorithm based on PCA and ANN: a real time study. Turk J Electr Eng & Comp Sci 2011; 19: 317-334.
[29] Eftekhari M, Moallem M, Sadri A, Hsieh MF. A novel indicator of stator winding inter-turn fault in induction motor using infrared thermal imaging. Infrared Phys Techn 2013; 61: 330-336.
[30] Kang M, Kim JM. Singular value decomposition based feature extraction approaches for classifying faults of induction motors. Mech Syst Signal Pr 2013; 41: 348-356.
[31] Foito D, Maia J, Fernao Pires V, Martins JF. Fault diagnosis in six-phase induction motor using a current trajectory mass center. Measurement 2014; 51: 164-173.
[32] Diamantaras KI. Neural networks and principal component analysis. In: Hu YH, Hwa JN, editors. Handbook of Neural Network Signal Processing. London, UK: CRC Press, 2001. Chapter 8.
[33] Eriksson L, Johansson E, Kettaneh-Wold N, Trygg J, Wikstr¨om C, Wold S. Multi and Megavariate Data Analysis. Part 1. Sweden: MKS Umetrics AB, 2006.
[34] Garcia-Alvarez D. Fault detection using principal component analysis (PCA) in a wastewater treatment plant (WWTP). In: International Forum 2009 Information and Communication Technologies and Higher Education Priorities of Modern Society Development; 26-30 May 2009; St. Petersburg, Russia.
[35] Jolliffe IT. Principal Component Analysis. New York, USA: Springer-Verlag, 2002.
[36] Ozg¨onenel O, Kılı¸c E. Modeling and realtime fault identification in transformers. J Frankl Inst 2008; 345: 205-225. ¨
[37] Gemperline PJ. Practical Guide to Chemometrics. 2nd ed. Boca Raton, FL, USA: CRC Press, 2006.
[38] Li D, Zhang Z, Wang H. Fault detection and diagnosis in activated effluent disposal process based on PCA. In: IEEE 2010 International Conference on Information and Automation; 20-23 June 2010; Harbin, China: IEEE. pp.216-221.