PSS with Multiple FACTS Controllers Coordinated Design and Real-Time Implementation Using Advanced Adaptive PSO

Authors: Rajendraprasad Narne, P. C. Panda

Abstract:

In this article, coordinated tuning of power system stabilizer (PSS) with static var compensator (SVC) and thyristor controlled series capacitor (TCSC) in multi-machine power system is proposed. The design of proposed coordinated damping controller is formulated as an optimization problem and the controller gains are optimized instantaneously using advanced adaptive particle swarm optimization (AAPSO). The objective function is framed with the inter-area speed deviations of the generators and it is minimized using AAPSO to improve the dynamic stability of power system under severe disturbance. The proposed coordinated controller performance is evaluated under a wide range of system operating conditions with three-phase fault disturbance. Using time domain simulations the damping characteristics of proposed controller is compared with individually tuned PSS, SVC and TCSC controllers. Finally, the real-time simulations are carried out in Opal-RT hardware simulator to synchronize the proposed controller performance in the real world.

Keywords: Advanced adaptive particle swarm optimization, Coordinated design, Power system stabilizer, Real-time implementation, static var compensator, Thyristor controlled series capacitor.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1090842

References:

[1] P. Kundur, Power System Stability and Control, McGraw-Hill, New York, 1994.
[2] P. M. Anderson, A. A. Fouad, Power system control and stability. Piscataway, N.J: Wiley-Interscience, 2003.
[3] G. Hingorani, L. Gyugyi, Understanding FACTS-Concepts and Technology of Flexible AC Transmission Systems, IEEE Press, New York, 2000.
[4] J. Kennedy, R. Eberhart, Particle Swarm Optimization, IEEE International Conference on Neural Networks, 4 (1995) 1942-1948.
[5] M. A. Abido, Optimal Design of Power–System Stabilizers Using Particle Swarm Optimization, IEEE Trans. Energy Conv., 17 (2002) 406-413.
[6] H. Shayeghi, H.A. Shayanfar, A. Safari, R. Aghmasheh, A robust PSSs design using PSO in a multi-machine environment, Energy Convers. Manage., 51 (2010) 696–702.
[7] M. A. Abido, Analysis of Power System Stability Enhancement via Excitation and Facts-Based Stabilizers, Elect. Power Compon. and Syst., 32 (2004) 75-91.
[8] Sidhartha Panda, Narayana Prasad Padhy, Comparison of particle swarm optimization and genetic algorithm for FACTS-based controller design, Applied Soft Computing, 8 (2008) 1418–1427.
[9] Xianzhang Lei, Edwin N. Lerch, Dusan Povh, Optimization and Coordination of Damping Controls for Improving System Dynamic Performance, IEEE Trans. Power Syst., 16 (2001) 473-480.
[10] Y.L. Abdel-Magid, M.A. Abido, Robust coordinated design of excitation and TCSC-based stabilizers using genetic algorithms, Electric Power Syst. Res., 69 (2004) 129–141.
[11] H. Shayeghi, H.A. Shayanfar, A. Safari, PSS and TCSC damping controller coordinated design using PSO in multi-machine power system, Energy Convers. Manage. 51 (2010) 2930–2937.
[12] E.S. Ali, S.M. Abd-Elazim, Coordinated design of PSSs and TCSC via bacterial swarm optimization algorithm in a multimachine power system, Int. J. Elect. Power and Energy Syst., 36 (2012) 84–92.
[13] X.Y. Bian, C.T. Tse, J.F. Zhang, K.W. Wang, Coordinated design of probabilistic PSS and SVC damping controllers, Int. J. Electrical Power and Energy Systems, 33 (2011) 445–452.
[14] S.M. Abd-Elazim, E.S. Ali, Coordinated design of PSSs and SVC via bacteria foraging optimization algorithm in a multimachine power system, Int. J. Elect. Power and Energy Syst., 41 (2012) 44–52.
[15] S.K. Tso, J. Liang, Q.Y. Zeng, K.L. Lo, X.X. Zhou, Coordination of TCSC and SVC for stability improvement of power systems, Pro. 4th Int. Conf. Advances in Power System Control, Operation and Management, Hong Kong, November 1997.
[16] S.K. Tso, J. Liang, X.X. Zhou, Coordination of TCSC and SVC for improvement of power system performance with NN-based parameter adaptation, Int. J. Elect. Power and Energy Syst., 21 (1999) 235–244.
[17] Xianzhang Lei, Edwin N. Lerch, Dusan Povh, Optimization and Coordination of Damping Controls for Improving System Dynamic Performance, IEEE Trans. Power Systems, 16 (2001) 473 - 480.
[18] K.T. Chaturvedi, M. Pandit, L. Srivastava, Self-organizing hierarchical particle swarm optimization for non-convex economic dispatch, IEEE Trans. Power Syst. 23 (2008) 1079–1087.
[19] Yu-hui Shi, Russell C Eberhart, Empirical study of particle swarm optimization, in Proc. IEEE Int. Congr. Evolutionary Computation, 3 (1999) 101–106.
[20] M.Clerc, J.Kennedy, The particle swarm - explosion, stability, and convergence in a multidimensional complex space, IEEE Trans. Evolutionary Computation, 6 (2002) 58–73.
[21] A. Ratnaweera, S.K. Halgamuge, H.C. Watson, Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients, IEEE Trans. Evol. Comput., 8(3) (2004) 240–255.
[22] Sidhartha Panda, Differentital evolutionary algorithm for TCSC-based controller design, Simulation Modelling Practice and Theory, 17 (2009) 1618-1634.
[23] J. Bélanger, V. Lapointe, C. Dufour, L. Schoen. "eMEGAsim: An Open High-Performance Distributed Real- Time Power Grid Simulator. Architecture and Specification. Presented at the International Conference on Power Systems (ICPS’07), Bangalore, India, (2007) 12-14.
[24] RT-LAB Professional, available: http://www.opal-rt.com/product/rt-lab-professional
[25] Mikkili. M, Panda AK. Simulation and real-time implementation of shunt active filter id–iq control strategy for mitigation of harmonics with different fuzzy membership functions. IET Power Electron 2012; 5(9): 1856–72.