Document Type : Review Article

Authors

The Faculty of Engineering, University of Urmia, Urmia, Iran

Abstract

The growing requirement to the clean and renewable energy has led to the rapid development of wind power systems all over the world. With increasing use of wind power in power systems, impact of the wind generators on sub-synchronous resonance (SSR) is going more important. The SSR is a well-known phenomenon in a series compensated power systems which can be mitigated with series or parallel flexible ac transmission systems (FACTS) devices. In this paper, wind turbines and steam turbines have been used as a hybrid energy production system. For damping the SSR, thyristor controlled series capacitor (TCSC) as a series FACT devise and unified power flow controller (UPFC) as a series-parallel FACT device have been used. In order to have an optimal control on pitch angle in high speed of wind, a novel method using imperialist competitive algorithm (ICA) has been used. Furthermore, supplementary controllers for UPFC and TCSC have been design and adaptive neuro fuzzy inference system (ANFIS) and fuzzy logic damping controllers (FLDC) are added to these FACTS devises to mitigate the SSR. Finally, the results of two FACTS devises have been compared. Furthermore, the results obtained from imperialist competitive algorithm (ICA) are compared with PID controller optimized by Particle Swarm Optimization (PSO) algorithm.

Keywords

[1] R. K. Varma, and S. Auddy, “Mitigation of Subsynchronous Oscillations in a Series Compensated Wind Farm with Static Var Compensator”, IEEE wer Engineering Society General Meeting, 2006.
[2] A. Rolan, A. Luna, G. R. Vazquez, D. Aguilar, and G. Azevedo. “Modeling of a Variable SpeedWind Turbine with a Permanent Magnet Synchronous Generator”. IEEE International Symposium on Industrial Electronics, 2009.
[3] P. Kundur, Power System Stability and Control. New York: McGraw-Hill, 1994.
[4] [4] L. A. S. Pilotto, A. Bianco, W. F. Long, and A. Edris, “IEEE Transactions on Power Delivery”, Vol. 18, No. 1, pp. 243 - 252, January 2003.
[5] [5] R. K. Varma, S. Auddy, and Y. Semsedini, “Mitigation of Subsynchronous Resonance in a Series-Compensated Wind Farm Using FACTS Controllers”, IEEE Transactions On Power Delivery, Vol. 23, No. 3, pp. 1645 - 1654, July 2008.
[6] [6]. IEEE Committee Rep., “First benchmark model for computersimulation of subsynchronous resonance,” IEEE Trans. Power Appl. Syst., vol. PAS- 96, no. 5, pp. 1565–1572, Sep./Oct. 1977.
[7] IEEE Subsynchronous Resonance Working Group, “Terms, definitions and symbols for subsynchronous oscillations,” IEEE Trans. Power Apparatus and Systems, vol. PAS-104, no. 6, pp. 1326–1334, 1985.
[8] K. R. Padiyar, Power System Dynamics: Stability and Control.Bangalore, India: Interline, 1996.
[9] IEEE SSR Working Group, Second Benchmark Model for Computer Simulation of Subsynchronous Resonance, IEEE Transaction on Power Apparatus and Systems. 104, No.5, PP.1057-1064, 1985.
[10] E. Uzunovic, C. A.Canizares, J. Reeve, “EMTP Studies of UPFC Power Oscillation Damping,” North American Power Symposium (NAPS) , San Luis Obisp o, California, October 1999.
[11] I.M. Hoseiny Naveh, E. Rakhshani, and R. Heidari, “Application of Linear Observer on Control of Subsynchronous oscillations Using TCSC,” IEEE, POWERENG, Lisbon, Portugal, pp. 540–545, March 2009.
[12] N. Muntean, O. Cornea, and D. Petrila, “A New Conversion and Control System for a Small off – Grid Wind Turbine,” 12th International Conference on Optimization of Electrical and Electronic Equipment, OPTIM, 2010.
[13] E. A. Gargari, and C. Lucas, “Imperialist Competitive Algorithm: An Algorithm for Optimization Inspires by Imperialistic Competition,” IEEE Congress on Evolutionary Computation, Singapore, 2007.
[14] A. M. Jasour, E. Atashpaz, and C. Lucas, “Vehicle Fuzzy Controller Design Using Imperialist Competitive Algorithm,” Second First Iranian Joint Congress on Fuzzy and Intelligent Systems, Tehran, Iran, 2008.
[15] N. Razmjooy, B. Somayeh musavi, B. Sadeghi, and M. Khalilpour, “Image Thresholding Optimization Based on Imperialist Competitive Algorithm,” 3rd Iranian Conference on Electrical and Electronics Engineering (ICEEE2011), 2011.
[16] J. Kennedy, R. Eberhart, “Particle swarm optimization,” in Proc.IEEE Int. Conf. Neural Networks, Vol. 4, Perth, ustralia, pp. 1942–1948, 1995.
[17] Q. Gu, A. Pandey, and S. K. Starrett, “Fuzzy Logic Control for SVC Compensator to Control System Damping Using Global Signal,” Electric Power Systems Research, Vol. 67, No. 1, pp. 115–122, 2003.
[18] H. He, “Fuzzy Modeling and Fuzzy Control [Book Review],” IEEE Computational Intelligence Magazine, 2008.
[19] R. C. Tatikonda , V. P. Battula, and V. Kumar, “Control of Inverted pendulum using Adaptive Neuro Fuzzy Inference Structure (ANFIS),” IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1348 – 1351, 2010.
[20] A. Khosla, S. Kumar, and K.K. Aggarwal, “Fuzzy Controller for Rapid Nickel-Cadmium Batteries Charger through Adaptive Neuro-Fuzzy Inference System (ANFIS) Architecture,” 22nd International Conference of the North American, uzzy Information Processing Society, pp. 540 – 544, 2003.
[21] S. R. Khuntia, and S. Panda, “ANFIS Approach for TCSC-based Controller Design for Power System Stability Improvement,” IEEE International Conference on Communication Control and Computing Technologies (ICCCCT), pp. 149 – 154, 2010.