An Intelligent Water Drop Algorithm for Solving Economic Load Dispatch Problem

Authors: S. Rao Rayapudi

Abstract:

Economic Load Dispatch (ELD) is a method of determining the most efficient, low-cost and reliable operation of a power system by dispatching available electricity generation resources to supply load on the system. The primary objective of economic dispatch is to minimize total cost of generation while honoring operational constraints of available generation resources. In this paper an intelligent water drop (IWD) algorithm has been proposed to solve ELD problem with an objective of minimizing the total cost of generation. Intelligent water drop algorithm is a swarm-based natureinspired optimization algorithm, which has been inspired from natural rivers. A natural river often finds good paths among lots of possible paths in its ways from source to destination and finally find almost optimal path to their destination. These ideas are embedded into the proposed algorithm for solving economic load dispatch problem. The main advantage of the proposed technique is easy is implement and capable of finding feasible near global optimal solution with less computational effort. In order to illustrate the effectiveness of the proposed method, it has been tested on 6-unit and 20-unit test systems with incremental fuel cost functions taking into account the valve point-point loading effects. Numerical results shows that the proposed method has good convergence property and better in quality of solution than other algorithms reported in recent literature.

Keywords: Economic load dispatch, Transmission loss, Optimization, Valve point loading, Intelligent Water Drop Algorithm.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1077207

References:

[1] A. J. Wood and B. F. Wollenberg, "Power generation operation and control", John Wiley and Sons, New York, 1984
[2] J. B. Park, K. S. Lee, J. R. Shin and K. Y. Lee, "A particle swarm optimization for economic dispatch with non smooth cost functions", IEEE Trans. on Power Systems, Vol. 8, No. 3, pp. 1325-1332, Aug. 1993.
[3] H. T. Yang, P. C. Yang and C. L. Huang, "Evolutionary Programming Based Economic Dispatch For Units With Non-smooth Fuel Cost Functions", IEEE Transactions on Power Systems, Vol. 11, No. 1, pp. 112-118, 1996.
[4] T. Jayabarathi, G. Sadasivam and V. Ramachandran, "Evolutionary programming based economic dispatch of generators with prohibited operating zones", Electric Power Systems Research, Vol. 52, No. 3, pp. 261-266, 1999.
[5] Z. X. Liang and J. D. Glover, "A zoom feature for a dynamic programming solution to economic dispatch including transmission losses, IEEE Trans. on Power Systems, Vol. 7, No. 2, pp. 544-550, May 1992.
[6] El-Sharkawy, M., and Nieebur, D., "Artificial neural networks with application to power systems", IEEE Power Engineering Society, A Tutorial Course, 1996.
[7] Yalcinoz, T., and Short, M. J., "Neural networks approach for solving economic dispatch problem with transmission capacity constraints", IEEE Trans. on Power Systems, Vol. 13, pp. 307-313, 1998.
[8] K.Y. Lee, A. Sode-Yome, J.H. Park, "Adaptive hopfield neural networks for economic load dispatch", IEEE Trans. on Power Systems, Vol.13, No. 2, pp. 519526, 1998.
[9] J.H. Park,Y.S. Kim, I.K. Eom, K.Y. Lee, "Economic load dispatch for piecewise quadratic cost function using Hop field neural network", IEEE Trans. on Power Systems, Vol. 8, No. 3, pp. 10301038, 1993.
[10] Pancholi, R. K., and Swarup, K. S., "Particle swarm optimization for security constrained economic dispatch", International Conference on Intelligent Sensing and Information Processing, Chennai, India, pp. 712, 2004.
[11] Youssef, H. K., and El-Naggar, K. M., "Genetic based algorithm for security constrained power system economic dispatch", Electric Power Systems Research, Vol. 53, pp. 4751, 2000.
[12] S.O. Orero, M.R. Irving, "Economic dispatch of generators with prohibited operating zones: a genetic algorithm approach", IEE Proc. Gen. Transm. Distrib., Vol. 143, No. 6, pp. 529534, 1996.
[13] D. C. Walters and G. B. Sheble, "Genetic algorithm solution of economic dispatch with the valve-point loading", IEEE Trans. on Power Systems, Vol. 8, No. 3, pp. 1325-1332, Aug. 1993.
[14] Nasimul Nomana, Hitoshi Iba, "Differential evolution for economic load dispatch problems", Electric Power Systems Research, Vol. 78, pp. 13221331, 2008.
[15] W. M. Lin, F. S. Cheng and M. T. Tsay, "An improved Tabu search for economic dispatch with multiple minima", IEEE Trans. on Power Systems, Vol. 17, No. 1, pp.108-112, Feb. 2002.
[16] Aniruddha Bhattacharya, P.K. Chattopadhyay, "Solving complex economic load dispatch problems using biogeography-based optimization", Expert Systems with Applications, Vol. 37, pp. 36053615, 2010.
[17] Hamed Shah-Hosseini, "The intelligent water drops algorithm: a natureinspired swarm-based optimization algorithm", International Journal of Bio-Inspired Computation, Vol. 1, Nos. 1 and 2, pp. 71-79, 2009.
[18] Shah-Hosseini. H, "Optimization with the Nature- Inspired Intelligent Water Drops Algorithm", Int. Journal of Intelligent Computing and Cybernetics, Vol. 1, No. 2, pp. 193-212, 2008.
[19]
[25] Z. Michalewicz, M. Schoenauer, "Evolutionary algorithms for constrained parameter optimization problems", Evol. Comput. vol. 4, no. 1, pp. 1-32, 1996.
[20] Gaing ZL, "Particle swarm optimization to solving the economic dispatch considering the generator constraints", IEEE Trans. on Power Systems, Vol. 18, No. 3, pp. 118795, 2003.
[21] Su CT, Lin CT, "New approach with a Hop field modeling framework to economic dispatch", IEEE Trans. on Power Systems, Vol. 15, No. 2, pp. 541545, 2000.