Solving Security Constrained Unit Commitment by Particle Swarm Optimization

Subject Areas : journal of Artificial Intelligence in Electrical Engineering

Shiva Alipour Ghorbani ¹ , Hossein Nasiraghdam ²

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Received: 2016-02-21 Accepted : 2015-02-21 Published : 2016-09-01

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References:

[1] Wood, A.J and Wollenberg, B.F. (1966). Power generation, operation and control, 2nd edi., Chapter 5, New York: Wiley., 131–170.

[2] Ouyang, Z., and Shahidehpour, S.M . (1991). An intelligent dynamic programming for unit commitment application, IEEE Trans. Power Syst., Vol. 6(3), 1203–1209.

[3] R. Baldik, Feb. (1995). " The generalized unit commitment problem," IEEE Trans. Power Syst., VOL. 10,pp. 465-475.

[4] Selvakumar, A. I. and Thanushkodi, k. (2007). A New Particle Swarm Optimization Solution to Nonconvex Economic Dispatch Problems, IEEE Transaction on Power System, VOL. 22, No. 1, pp. 42-51.

[5] Bai, X., Wei, H. (2007). Semi-definite Programming-based method for securityconstrained unit commitment with operational and optimal power flow constraints, Coll. of Electr. Eng., Guangxi Univ. Vol. 3, pp. 1751- 8687.

[6] Zhao., Wang., J., Watson., p. J. and Guan., Y. (2013). Multi-stage robust unit commitment considering wind and demand response uncertainties. IEEE Transaction on Power Systems; 28: 52-63., 2013.

[7] Chandrasekaran., K. and Simon. S. P. (2013). Optimal deviation based firefly algorithm tuned fuzzy design for multi-objective UCP”. IEEE Transaction on Power Systems; 28: 460-471.