An Improved Mean-Variance Optimization for Nonconvex Economic Dispatch Problems

- Journal title : Journal of Electrical Engineering and Technology
- Volume 8, Issue 1, 2013, pp.80-89
- Publisher : The Korean Institute of Electrical Engineers
- DOI : 10.5370/JEET.2013.8.1.080

Title & Authors

An Improved Mean-Variance Optimization for Nonconvex Economic Dispatch Problems

Kim, Min Jeong; Song, Hyoung-Yong; Park, Jong-Bae; Roh, Jae-Hyung; Lee, Sang Un; Son, Sung-Yong;

Kim, Min Jeong; Song, Hyoung-Yong; Park, Jong-Bae; Roh, Jae-Hyung; Lee, Sang Un; Son, Sung-Yong;

Abstract

This paper presents an efficient approach for solving economic dispatch (ED) problems with nonconvex cost functions using a `Mean-Variance Optimization (MVO)` algorithm with Kuhn-Tucker condition and swap process. The aim of the ED problem, one of the most important activities in power system operation and planning, is to determine the optimal combination of power outputs of all generating units so as to meet the required load demand at minimum operating cost while satisfying system equality and inequality constraints. This paper applies Kuhn-Tucker condition and swap process to a MVO algorithm to improve a global minimum searching capability. The proposed MVO is applied to three different nonconvex ED problems with valve-point effects, prohibited operating zones, transmission network losses, and multi-fuels with valve-point effects. Additionally, it is applied to the large-scale power system of Korea. The results are compared with those of the state-of-the-art methods as well.

Keywords

Nonconvex optimization;Economic dispatch;Mean-variance optimization;Kuhn-Tucker condition;

Language

English

Cited by

1.

2.

3.

References

1.

K. Y. Lee and M. A. El-Sharkawi (Editors), Modern Heuristic Optimization Techniques with Applications to Power Systems, IEEE Power Engineering Society (02TP160), 2002.

2.

A. J. Wood and B. F. Wollenberg, Power Generation, Operation, and Control. New York: John Wiley & Sons, Inc., 1984.

3.

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

4.

C. E. Lin and G. L. Viviani, "Hierarchical economic dispatch for piece-wise quadratic cost functions," IEEE Trans. Power App. Syst., Vol. PAS-103, No.6, pp. 1170-1175, June 1984.

5.

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.

6.

S. O. Orero and M. R. Irving, "Economic dispatch of generators with prohibited operating zones: a genetic algorithm approach," IEE Proc.-Gener. Transm. Distrib., Vol. 143, No. 6, pp. 529-534, Nov. 1996.

7.

C. L. Chiang, "Improved genetic algorithm for power economic dispatch of units with valve-point effects and multiple fuels," IEEE Trans. on Power Systems, Vol. 20, No. 4, pp. 1690-1699, Nov. 2005.

8.

H. T. Yang, P. C. Yang, and C. L. Huang, "Evolutionary programming based economic dispatch for units with non-smooth fuel cost functions," IEEE Trans. on Power Systems, Vol. 11, No. 1, pp. 112- 118, Feb. 1996.

9.

Y. M. Park, J. R. Won and J. B. Park, "A new approach to economic load dispatch based on improved evolutionary programming," Engineering Intelligent Systems for Electrical Engineering and Communications, Vol. 6, No. 2, pp. 103-110, June 1998.

10.

N. Sinha, R. Chakrabarti, and P. K. Chattopadhyay, "Evolutionary programming techniques for economic load dispatch," IEEE Trans. on Evolutionary Computations, Vol. 7, No. 1, pp. 83-94, Feb. 2003.

11.

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.

12.

J. H. Park, Y. S. Kim, I. K. Eom, and K. Y. Lee, "Economic load dispatch for piecewise quadratic cost function using Hopfield neural network," IEEE Trans. on Power Systems, Vol. 8, No. 3, pp. 1030-1038, August 1993.

13.

K. Y. Lee, A. Sode-Yome, and J. H. Park, "Adaptive Hopfield neural network for economic load dispatch," IEEE Trans. on Power Systems, Vol. 13, No. 2, pp. 519-526, May 1998.

14.

L. S. Coelho and V. C. Mariani, "Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valvepoint effect," IEEE Trans. on Power Systems, Vol. 21, No. 2, May 2006.

15.

Z. L. Gaing, "Particle swarm optimization to solving the economic dispatch considering the generator constraints," IEEE Trans. on Power Systems, Vol. 18, No. 3, pp. 1187-1195, Aug. 2003.

16.

J. B. Park, K. S. Lee, J. R. Shin, and K. Y. Lee, "A particle swarm optimization for economic dispatch with nonsmooth cost functions," IEEE Trans. on Power Systems, Vol. 20, No. 1, pp. 34-42, Feb. 2005.

17.

T. A. A. Victoire and A. E. Jeyakumar, "Hybrid PSO-SQP for economic dispatch with valve-point effect," Electric Power Systems Research, Vol. 71, pp. 51-59, Sep. 2004.

18.

A. I. Selvakumar and K. Thanushkodi, "A new particle swarm optimization solution to nonconvex economic dispatch problems," IEEE Trans. on Power Systems, Vol. 22, No. 1, pp. 42-51, Feb. 2007.

19.

W. M. Lin, F. S. Cheng, and M. T. Tsay, "Nonconvex economic dispatch by integrated artificial intelligence," IEEE Trans. on Power Systems, Vol. 16, No. 2, pp. 307-311, May 2001.

20.

J. B. Park, Y. W. Jeong, J. R. Shin, and K. Y. Lee, "An improved particle swarm optimization for nonconvex economic dispatch problems," IEEE Trans. on Power Systems, Vol. 25, No. 1, pp. 156-166, Feb. 2010.

21.

H. Y. Song, Y. G. Park, J. H. Roh, J. B. Park, "Immune-PSO for economic dispatch with valve point effect," Advanced Materials Research, Vol. 452-453, pp. 1054-1058, 2012.

22.

Erlich. I, Venayagamoorthy. G. K, Worawat. N, "A mean-variance optimization algorithm," IEEE World Congress on Computational Intelligence, pp. 344-349, July. 2010