AUTHORS: A. Y. Hatata, M. Eladawy, K. Shebl
Download as PDF
ABSTRACT: This paper presents a shunt active power filter control reference signal using Nonlinear Autoregressive with eXogenous neural network (NARX) with back propagation training algorithm. The instantaneous reactive power algorithm is integrated within the neural network to extract the dominant harmonics. The proposed method is demonstrated on three phase thyristor controlled drive which is one of widely used loads in petroleum industry field
KEYWORDS: NARX Neural Network; Nonlinear Loads; Shunt Active Power Filter; Instantaneous Reactive Power Algorithm
REFERENCES:
[1] A. Baggini, Handbook of Power Quality, V. V. Thong, J. Driesen Ch. 16, Distributed Generation and Power Quality, John Wiley, 2008.
[2] H. Akagi, Instantaneous Power Theory and Applications to Power Conditioning, Hoboken: John Wiley Sons, 2007.
[3] B. Singh, K. Al Haddad and A. Chandra, A review of active filters for power quality improvement, Industrial Electronics, IEEE Transactions on, Vol. 46, pp. 960-971, 1999.
[4] A. Emadi, A. Nasiri, and S. B. Bekiarov, Uninterruptible Power Supplies and Active Filters, Boca Raton, FL: CRC Press, ISBN: 0 8493-3035-1, Oct. 2004.
[5] H. Akagi, Trends in active power line conditioners, IEEE Industrial Electronics, Control, Instrumentation, and Automation, Vol. 1, 1992, pp. 1924.
[6] B. N. Singh, A. Chandra, and K. Al-Haddad, A new control scheme of series hybrid active filter, 30th IEEE Power Electronics Specialists Conference, Vol. 1, 1999, pp. 249254.
[7] H. Fujita, and H. Akagi, The unified power quality conditioner: the integration of seriesand shunt-active filters, IEEE Transactions on Power Electronics, 13 (2), 315322, 1998.
[8] H. Akagi, Active and hybrid filters for power conditioning, IEEE Conference on Industrial Electronics, Vol. 1, 2000, pp. TU26TU36.
[9] P. Salmeron and J. R. Vazquez, Practical design of a three phase active power line conditioner controlled by artificial neural networks, IEEE Transactions on Power Delivery, Vol. 20, 2, pp.1037-1044, April 2005.
[10] P. Cheng, S. Bhattacharya and D. Divan, Experimental verification of dominant harmonic active filter for high power applications, IEEE Transactions on Industry Applications, Vol. 36, pp.567-577, March/April 2000.
[11] J. Mazumdar, System and method for determining harmonic contributions from nonlinear loads in power systems, Georgia Institute of Technology Dec. 2006.
[12] M. U. Hashmi, V. Arora, J. G. Priolkar, Hourly electric load forecasting using Nonlinear AutoRegressive with eXogenous (NARX) based neural network for the state of Goa, India, Industrial Instrumentation and Control (ICIC), 2015 International Conference on Year: 2015, Pp. 1418 - 1423, IEEE Conference Publications.
[13] Y. Liu, X. Wang, Y. Liu, Asynchronous harmonic analysis based on out-of-sequence measurement for large scale residential power network, Instrumentation and Measurement Technology Conference (I2MTC), 2015, pp. 1693 1698, IEEE Conference Publications
[14] H. T. Siegelmann, and E. D. Sontag, Turing Computability with Neural Nets, Applied Mathematics Letters, Vol. 4, 1991, pp. 77-80.
[15] M. T. Hagan, H. B. Demuth, M. H. Beale, Neural Network Design, Jan 2002
[16] M. H. Beale, M. T. Hagan, H. B. Demuth, Neural Network Toolbox 7 User s Guide.