Applying Sequential Particle Swarm Optimization Algorithm to Improve Power Generation Quality

Authors

  • Abdulhafid Sallama
  • Maysam Abbod
  • Shariq Mahmood Khan

Keywords:

Particle swarm optimization, Fuzzy logic controller, Power system stabilizer and Adaptive neuro fuzzy interference system, Multi band stabilizer.

Abstract

Swarm Optimization approach is a heuristic search method whose mechanics are inspired by the swarming or collaborative behaviour of biological populations. It is used to solve constrained, unconstrained, continuous and discrete problems. Swarm intelligence systems are widely used and very effective in solving standard and large-scale optimization, provided that the problem does not require multi solutions. In this paper, particle swarm optimisation technique is used to optimise fuzzy logic controller (FLC) for stabilising a power generation and distribution network that consists of four generators. The system is subject to different types of faults (single and multi-phase). Simulation studies show that the optimised FLC performs well in stabilising the network after it recovers from a fault. The controller is compared to multi-band and standard controllers.

References

V. Rupal, H. A. Patel, and A. Mehta “Novel approach for designing a power system stabilizer,” National Conference on Recent Trends in Engineering & Technology, May 2011.

K. D. Koper, M. E. Wysession and D. A. Wiens, "Multimodal function optimization with a niching genetic algorithm: A seismological example," Bulletin of the Seismological Society of America, vol. 89, pp. 978-988, August 01, 1999.

K. S. Hook, Y. Liu, and S. Atcitty, “Mitigation of the wind generation integration related power quality issues by energy storage,” EPQU J., vol. XII, no. 2, 2006.

F. W. Keay and W. H. South, “Design of power system stabilizer sensing frequency deviation,” IEEE Transactions on Power Apparatus and Systems, vol. 90, pp.707- 713, March 1971.

C. J. Wu and Y. Y. Hsu, “Design of self-tuning PID power system stabilizer for multimachine Power System,” IEEE Transactions on Power Systems, vol. 3, pp. 1059-1064, Aug. 1998.

C. C. Lee, “Fuzzy logic in control systems—Part I and II,” IEEE Trans.Syst., Man, Cybern., vol. 20, pp. 404-435, Mar./Apr. 1990.

K. A. El-Metwally and O. P. Malik, “Fuzzy logic based power system stabilizer,” IEEE Proc- Gener.Transm. Distri., vol. 142, pp.277-281, May 1995.

A. Afzalian, and D. A. Linkens, “Training of neurofuzzy power system stabilisers Using Genetic Algorithms,” International-Journal-of-Electrical-Power-&-Energy-Systems, vol. 22, no. 2, pp. 93-102, 2000.

J. Kennedy and R. Eberhart, "Particle swarm optimization," in Neural Networks, 1995, Proceedings, IEEE International Conference on, vol.4, pp. 1942-1948, 1995.

D. Bratton and J. Kennedy, "Defining a standard for particle swarm optimization," in Swarm Intelligence Symposium, 2007, SIS 2007, IEEE, pp. 120-127, 2007.

C. W. Reynolds, "Flocks, herds and schools: A distributed behavioral model," in ACM SIGGRAPH Computer Graphics, pp. 25-34, 1987.

R. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Micro Machine and Human Science, 1995, MHS '95, Proceedings of the Sixth International Symposium on, pp. 39-43, 1995.

J. Kennedy and R. C. Eberhart, "A discrete binary version of the particle swarm algorithm," in Systems, Man, and Cybernetics, 1997, Computational Cybernetics and Simulation, 1997 IEEE International Conference on, pp. 4104-4108, vol. 5, 1997.

Y. Shi and R. Eberhart, "A modified particle swarm optimizer," in Evolutionary Computation Proceedings, 1998, IEEE World Congress on Computational Intelligence, the 1998 IEEE International Conference on, pp. 69-73, 1998.

J. J. Liang, A. K. Qin, P. N. Suganthan and S. Baskar, "Comprehensive learning particle swarm optimizer for global optimization of multimodal functions," Evolutionary Computation, IEEE Transactions on, vol. 10, pp. 281-295, 2006.

J. J. Liang and P. N. Suganthan, "Dynamic multi-swarm particle swarm optimizer," in Swarm Intelligence Symposium, 2005, SIS 2005, Proceedings 2005 IEEE, pp. 124-129, 2005.

S-Z. Zhao, P. N. Suganthan and S. Das, "Dynamic multi-swarm particle swarm optimizer with sub-regional harmony search," in Evolutionary Computation (CEC), 2010 IEEE Congress on, pp. 1-8, 2010.

Z-H. Zhan, Jun Zhang, Yun Li and H-S. Chung, "Adaptive particle swarm optimization," Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, vol. 39, pp. 1362-1381, 2009.

K. E. Parsopoulos and M. N. Vrahatis, "Unified particle swarm optimization for tackling operations research problems," in Swarm Intelligence Symposium, 2005, SIS 2005, Proceedings 2005 IEEE, pp. 53-59, 2005.

I. Kamwa, R. Grondin, and G. Trudel, “IEEE PSS2B versus PSS4B: the limits of performance of modern power system stabilizers,” IEEE Trans. Power Systems, vol. 20, pp. 903-914, May 2005.

H. P. Inamdar and R. P. Hasabe, “It based energy management through demand side in the industrial sector,” INCACEC International Conference on Control, Automation, Communication and Energy Conservation, pp. 1-7, 2009.

A. T. Ali, E. B. M. Tayeb and M. K. A. Adam, "A multi-machine power system stabilizer using fuzzy logic controller," International Journal of Computational Engineering Research, vol. 2, Issue. 6, Oct 2012.

H. Bevrani, and P. Ranjbar, “Fuzzy logic-based load-frequency control concerning high penetration of wind turbines,” IEEE Systems Journal, 2011.

T. P. Hong and C. Y. Lee, “Induction of fuzzy rules and membership functions from training examples,” Fuzzy Sets and Systems, vol. 84, pp. 33-47, Nov. 1996.

J. Machowski, J. Bialek, and J. Bumby. Power system dynamics: stability and control, John Wiley & Sons, 2011.

Z-H. Zhan, J. Zhang, Y. Li, and H. S-H. Chung, “Adaptive particle swarm optimization,” IEEE Transactions on Systems Man, and Cybernetics. Part B: Cybernetics, vol. 39, no. 6, pp. 1362-1381, 2009.

H. Jiang, J. Zheng, L. Chen, “A particle swarm algorithm for multiobjective optimization problem,” Journal of Pattern Recognition and Artificial Intelligence, vol. 20, pp. 606-611, 2007.

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Published

2014-10-01

How to Cite

[1]
A. Sallama, M. Abbod, and S. M. Khan, “Applying Sequential Particle Swarm Optimization Algorithm to Improve Power Generation Quality”, Int. j. eng. technol. innov., vol. 4, no. 4, pp. 223–233, Oct. 2014.

Issue

Vol. 4 No. 4 (2014)

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Articles

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