Thermal Unit Commitment Using Binary Differential Evolution

- Journal title : Journal of Electrical Engineering and Technology
- Volume 4, Issue 3, 2009, pp.323-329
- Publisher : The Korean Institute of Electrical Engineers
- DOI : 10.5370/JEET.2009.4.3.323

Title & Authors

Thermal Unit Commitment Using Binary Differential Evolution

Jeong, Yun-Won; Lee, Woo-Nam; Kim, Hyun-Houng; Park, Jong-Bae; Shin, Joong-Rin;

Jeong, Yun-Won; Lee, Woo-Nam; Kim, Hyun-Houng; Park, Jong-Bae; Shin, Joong-Rin;

Abstract

This paper presents a new approach for thermal unit commitment (UC) using a differential evolution (DE) algorithm. DE is an effective, robust, and simple global optimization algorithm which only has a few control parameters and has been successfully applied to a wide range of optimization problems. However, the standard DE cannot be applied to binary optimization problems such as UC problems since it is restricted to continuous-valued spaces. This paper proposes binary differential evolution (BDE), which enables the DE to operate in binary spaces and applies the proposed BDE to UC problems. Furthermore, this paper includes heuristic-based constraint treatment techniques to deal with the minimum up/down time and spinning reserve constraints in UC problems. Since excessive spinning reserves can incur high operation costs, the unit de-commitment strategy is also introduced to improve the solution quality. To demonstrate the performance of the proposed BDE, it is applied to largescale power systems of up to 100-units with a 24-hour demand horizon.

Keywords

Combinatorial optimization;unit commitment;binary differential evolution;constrainthandling;

Language

English

Cited by

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References

1.

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

2.

Burns, R. M., and Gibson, C. A., 'Optimization of priority lists for a unit commitment program', Proc. IEEE Power Engineering Society Summer Meeting,
Paper A, 75 453-1, 1975

3.

Sheble, G. B., 'Solution of the unit commitment problem by the method of unit periods', IEEE Trans. on Power Systems, Vol. 5, No. 1, pp. 257-260, Feb. 1990

4.

Snyder Jr., W. L., Powell Jr., H. D., and Rayburn, J. C., 'Dynamic programming approach to unit commitment' IEEE Trans. on Power Apparatus and Systems, Vol. PAS-2, pp. 339-350, May 1987

5.

Ouyang, Z., and Shahidehpour, S. M., 'An intelligent dynamic programming for unit commitment application', IEEE Trans. on Power Systems, Vol. 6, No. 3, pp. 1203-1209, Aug. 1991

6.

Merlin, A., and Sandrin, P., 'A new method for unit commitment at Electricite de France', IEEE Trans. on Power Apparatus and Systems, Vol. PAS-102, pp. 1218-1255, May 1983

7.

Zhuang, F., and Galiana, F. D., 'Toward a more rigorous and practical unit commitment by Lagrangian relaxation', IEEE Trans. on Power Systems, Vol. 3, No. 2, pp. 763-770, May 1988

8.

Cohen, A. I., and Yoshimura, M., 'A branch-andbound algorithm for unit commitment', IEEE Trans. on Power Apparatus and Systems, Vol. PAS-102, pp. 444-451, Feb. 1983

9.

Muckstadt, J. A., and Wilson, R. C., 'An application of mixed-integer programming duality to scheduling thermal generating systems', IEEE Trans. on Power Apparatus and Systems, pp. 1968-1978, 1968

10.

Kazarlis, S. A., Bakirtzis, A. G., and Petridis, V., 'A genetic algorithm solution to the unit commitment problem', IEEE Trans. on Power Systems, Vol. 11, No. 1, pp. 83-92, Feb. 1996

11.

Swarup, K. S., and Yamashiro, S., 'Unit commitment solution methodology using genetic algorithm', IEEE Trans. on Power Systems, Vol. 17, pp. 87-91, Feb. 2002

12.

Juste, K. A., Kita, H., Tanaka, E., and Hasegawa, J., 'An evolutionary programming solution to the unit commitment problem', IEEE Trans. on Power Systems, vol. 14, pp. 1452-1459, Nov. 1999

13.

Chen, H, and Wang, X., 'Cooperative coevolutionary algorithm for unit commitment', IEEE Trans. on Power Systems, vol. 16, pp. 128-133, Feb. 2002

14.

Zhuang, F., and Galiana, F. D., 'Unit commitment by simulated annealing', IEEE Trans. on Power Systems, Vol. 5, No. 1, pp. 311-317, Feb. 1990

15.

Simopoulos, D. N., Kavatza, S. D., and Vournas, C. D., 'Unit commitment by an enhanced simulated annealing algorithm', IEEE Trans. on Power Systems, Vol. 21, No. 1, pp. 68-76, Feb. 2006

16.

Zhao, B., Guo, C. X., Bai, B. R., and Cao, Y. J., 'An improved particle swarm optimization algorithm for unit commitment', Electrical Power & Energy Systems,
Vol. 28, Issue 7, pp. 482-490, Sep. 2006

17.

Storn, R., and Price, K., 'Differential evolution – A simple and efficient heuristic for global optimization over continuous spaces', Journal of Global Optimization, Vol. 11, pp. 341-359, 1997

18.

Chang, C. Wong, J., Chiou, J., and Su, C., 'Robust searching hybrid differential evolution method for optimal reactive power planning in large-scale distribution systems', Electric Power Systems Research, pp. 1-8, May 2006

19.

Arora, J.S., Introduction to Optimum Design, McGraw-Hill, Inc., 1989