Email this article 
Open Access
Subscription or Fee Access
Optimal Power Flow in Competitive Market Using Differential Evolution
Abstract
To meet the growing load demand, power industries throughout the world are undergoing restructured process in which the Independent Power Producers (IPP) must respond quickly to the load changes with respect to time. This paper describes the solution for Optimal Power Flow (OPF) in competitive market using Differential Evolution (DE)technique. The proposed approach is capable of obtaining minimum solution irrespective of the nature of the objective function. The effectiveness of the approach is compared with the performance of Particle Swarm Optimization technique and other published works. The obtained OPF solution satisfies the standard transient stability rotor/voltage criteria. The proposed algorithm has been demonstrated on IEEE 30 and Indian utility 62 bus systems with various case studies
Keywords
References
Yog Raj Sood, Narayana Prasad Padhy and H. O. Gupta, “Wheeling of Power under Deregulated Environment of Power System – A Bibliographical Survey”, IEEE Transactions on Power Systems, vol. 17, no. 3, August 2002, pp.870 – 878.
W. Ongsakul, T. Tantimapron “Optimal Power Flow by improved Evolutionary Programming”, Electric Power Components and Systems,vol. 34, 2006, pp.79 - 95.
J. A. Mamoh, M. E. EI-Hawary and R. Adapa, “A review of selected optimal power flow literature to 1993 Part I: Nonlinear and quadratic programming approaches”, IEEE Transactions on Power Systems, vol.14, no.1, February 1999, pp.96 - 104.
J. A. Mamoh, M. E. EI-Hawary and R. Adapa, “A review of selected optimal power flow literature to 1993 part II: Newton, linear programming and Interior point methods”, IEEE Transactions on Power Systems, vol. 14. no.1, February 1999, pp.105 – 111.
J. Yuryevich and K. P. Wong, “Evolutionary Programming based optimal power flow algorithm,” IEEE Transactions on Power Systems, vol. 14,no. 4, Nov 1999, pp.1245 – 1250.
P. Venkatesh, R. Gnanadass, and Narayana Prasad Padhy, “Comparison and application of Evolutionary Programming Techniques to combined Economic Emission Dispatch with Line constraints”, IEEE Transactions on Power Apparatus and systems,vol.18,no.2, May 2003, pp.688 – 697.
A. G. Bakirtzis, P. N. Biskas, C. E. Zoumas and V. Petridis, “Optimal Power Flow by enhanced Genetic Algorithm”, IEEE Transactions on Power Systems, vol. 17, no. 2, May 2002, pp. 229 – 236.
M. A. Abido, “Optimal Power Flow using Tabu Search algorithm”,Electric Power Components and Systems, vol. 30, no. 5, May 2002,,pp.469 – 483.
T. Kulworawanichpong and S. Sujitorn, “Optimal Power Flow using Tabu Search”, IEEE power Engineering Review, vol. 22, June 2002, pp.37 – 40.
C. A. Roa-Sepulveda and B. J. Power – Lazo, “A Solution to the Optimal Power Flow using Simulated Annealing”, Electrical Power and Energy Systems, vol. 25, no. 1, January 2003, pp. 47 – 57.
R.S Fang and A.K. David, “Optimal Dispatch under transmission contracts” IEEE transactions on power system”, vol.14, no.2, May 1999,pp.732 – 737.
Yog Raj Sood, Narayana Prasad Padhy and H. O. Gupta “Analysis and Management of Wheeling Transactions based on AI techniques under Deregulated environment of power sector”, Water and Energy International of Journal, vol. 58, no.1, Jan-March 2001, pp.45 -52.
M. A. Abido, “ Optimal Power Flow using Particle Swarm Optimization”, Electrical Power and Energy Systems, vol. 24, no.7,,September 2002 , pp.563 – 571.
J. Kennedy and R. C. Eberhart, “Particle swarm optimization”, in proceedings of the IEEE International conference on Neural Networks,vol.4, 1995, pp.1942-1948.
R. Gnanadass, “Optimal Dispatch and pricing for deregulated power industry”, PhD thesis Pondicherry Engineering college, Puducherry,India, July 2005.
R. Storn and K. Price, “Differential Evolution A Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces”,Technical Report JR – 95 – 012, ICSI, March 1995.
J. B. Park et al., “A Particle swarm optimization for Economic Dispatch with Non-smooth cost functions”, IEEE Transactions on Power systems,vol. 20, no.1, Feb 2005, pp.34-42.
J. Lampinen, “A Constraint handling Approach for the Differential Evolution Algorithm”, Proceedings of the Congress on Evolutionary computation, CEC’02, vol. 2, 2002.
K. Price, “Differential Evolution: A Fast and simple Numerical optimizer”, Biennial conference of the North American Fuzzy Information Processing society, pp.524 – 527, 1996.
R. Gamperie, S. Muller, et al., “A parameter study for Differential Evolution”, Advances in Intelligent systems, Fuzzy systems,Evolutionary computation, WSEAS Press, pp.293 - 298, 2002.
Z. Michalewiczm, M. Schoenauer, “Evolutionary Algorithm for constrained optimization problems”, International Journal of Evolutionary Computation, vol.4, no.1, 1996, pp.1-32.
K. P. Wong and Z. Y. Dong, “Differential Evolution, an Alternative approach to Evolutionary Algorithm”, in K. Y. Lee et al., “Intelligent optimization and control for power systems” IEEE Publishing invited chapter Nov. 2005.
K. Price, “An introduction to Differential Evolution”, New optimization,(Eds) D. Corne, M. Dorigo et al., London, Mcgraw Hill International (UK) Limited, pp.79 -108, 1999.
Indian Energy Exchange limited (www.iexindia.com)
NERC Planning Standards( http://www.nerc.com)
D. J. Shoup, J. Paserba and C. W. Taylor, “A Survey of Current Practices for Transient Voltage Dip/Sag Criteria Related to Power System Stability” IEEE Power system Conference and Exposition, Vol. II, pp.1140 – 1147, Oct. 10 13, 2004.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.