Abstract
This paper presents a fault identification system for doubly fed induction generator (DFIG). It considers cases of single phase short-circuits and load switching. The system uses the fast fourier transform (FFT) to preprocessor data, which consist by the stator line currents. The principal component analysis (PCA) is employed to reduce the dimensionality of the output data of FFT and the fault identification is made by means of artificial neural network (ANN). Also, a post-processing (PP) is employed in order to increase the network reliability, which reduces the error of ANN. The system is simulated in the MATLAB simulation software using a database with different voltage, speed and load. The results show that the system with PCA, FFT and ANN has a good performance and accuracy with the PP to fault identification in the DFIG.
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References
Alaya, J.B., Khedher, A., Mimouni, M.F.: Nonlinear vector control strategy applied to a variable speed DFIG generation system. In: Eighth International Multi-Conference on Systems, Signals & Devices, pp. 1–8 (2011)
Boldea, I.: Variable speed generators. Taylor&Francis, Timisoaria (2006)
El-helw, H.M., Tennakoon, B.S.: Vector Control of a Doubly Fed Induction Generator for Standalone Wind Energy Application. In: 2008 Wind Power to the Grid, EPE Wind Energy Chapter, pp. 1–6 (2008)
Lesic, V., Vasak, M., Peric, N., Wolbank, T., Joksimovic, G.: Fault-tolerant control of a blade-pitch wind turbine with inverter-fed generator. In: 1st IEEE International Symposium on Industrial Electronics, pp. 12097–12102 (2011)
Henao, H., Capolino, G.A., Casadei, D., Filippetti, F., Rossi, C.: Simulation of a doubly-fed induction machine for wind turbine generator fault analysis. In: 5th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, pp. 1–6 (2005)
Heraud, N., Guelle, I.S., Bennouna, O.: Fault diagnosis of variable speed wind turbine. In: 18th Mediterranean Conference on Control and Automation, Marrakech, Morocco, pp. 471–476 (2010)
Ramroop, S.A.D.: Fault detection of fault ride through for doubly-fed induction generator based wind energy systems. Master’s thesis, Ryerson University, Toronto (2008)
Rothenhagen, K., Fuchs, F.W.: Grid Information Services for Distributed Resource Sharing. In: Current Sensor Fault Detection, Identification, and Reconfiguration for Doubly Fed Induction Generators, Taipei, Taiwan, pp. 1115–1120 (2007)
Barbi, I.: Teoria fundamental do motor de indução. Editora da UFSC, Florianopolis (1985)
Krause, P.C., Wasynczuk, O.S., Scott, D.: Analysis of electric machinery and drive systems. IEEE Press and Wiley-Interscience, NY (2002)
Leng, P., Yongdong, L., Jianyun, C., Guofeng, Y.: Vector control of a doubly fed induction generator for stand-alone ship shaft generator systems. In: Electrical Machines and Systems-ICEMS, Seoul, Korea, pp. 1033–1036 (2007)
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de Santana, M.P., de Almeida Monteiro, J.R.B., de Paula, G.T., de Almeida, T.E.P., Romero, G.B., Faracco, J.C. (2012). Fault Identification in Doubly Fed Induction Generator Using FFT and Neural Networks. In: Yin, H., Costa, J.A.F., Barreto, G. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2012. IDEAL 2012. Lecture Notes in Computer Science, vol 7435. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32639-4_83
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DOI: https://doi.org/10.1007/978-3-642-32639-4_83
Publisher Name: Springer, Berlin, Heidelberg
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