Unit commitment using a new integer coded genetic algorithm

European Transactions on Electrical Power

Volumn 19, Issue 8, 2009, Pages 1161-1176

  Amjady, Nima ^a   Shirzadi, Ali ^a  

^a SEMNAN UNIVERSITY   (Iran)

Author keywords

Crossover; Integer coded genetic algorithm; Mutation; Unit commitment

Indexed keywords

CHROMOSOME STRUCTURE; DOWN TIME; GENERATING UNIT; INTEGER NUMBERS; INTEGER-CODED GENETIC ALGORITHM; MUTATION OPERATORS; NON-UNIFORM MUTATION; OPERATION COST; TEST RESULTS; THERMAL GENERATING UNITS; THERMAL UNITS; UNIT COMMITMENTS;

GENETIC ALGORITHMS;

MATHEMATICAL OPERATORS;

EID: 73649119873     PISSN: 1430144X     EISSN: 15463109     Source Type: Journal    
DOI: 10.1002/etep.297     Document Type: Article

References (38)

1. Wood AJ, Wollenberg BF. Power Generation, Operation, and Control, 2nd edn. Wiley: New York, 1996.
2. Gollmer R, Nowak MP, RomischW, Schultz R. Unit commitment in power generation-a basic model and some extensions. Annals of Operation Research 2000; 96: 167-189.
3. Shahidehpour M, Yamin H, Li Z. Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management. Wiley: New York, 2002; 275-310.
4. Federal Energy Regulatory Commission. Remedying undue discrimination through open access transmission service and standard electricity market design. Notice of proposed rulemaking. Document No. RM01-12-000. June 2002. Available online at: http://www.ferc.gov/.
5. Hosseini SH, Khodaei A, Aminifar F. A novel straightforward unit commitment method for large-scale power systems. IEEE Transactions on Power Systems 2007; 22(4): 2134-2143.
6. Senjyu T, Shimabukuro K, Uezato K, Funabashi T. A fast technique for unit commitment problem by extended priority list. IEEE Transactions on Power Systems 2003; 18(2): 882-888.
7. Senjyu T, Miyagi T, Saber AY, Urasaki N, Funabashi T. Emerging solution of large-scale unit commitment problem by stochastic priority list. Electric Power Systems Research 2006; 76: 283-292.
8. Snyder WL, Powell HD, Rayburn JC. Dynamic programming approach to unit commitment. IEEE Transactions on Power Systems 1987; 2(2): 339-350.
9. Ongsakul W, Petcharaks N. Unit commitment by enhanced adaptive Lagrangian relaxation. IEEE Transactions on Power Systems 2004; 19(1): 620-628.
10. Cohen AI, Yoshimura M. A branch-and-bound algorithm for unit commitment. IEEE Transactions on Power Systems 1983; PAS-102(2): 444-451.
11. Dillon TS, Edwin KW. Integer programming approach to the problem of optimal unit commitment with probabilistic reserve determination. IEEE Transactions on Power Systems 1978; PAS-97(6): 2154-2166.
12. Carrión M, Arroyo JM. A Computationally efficient mixed-integer linear formulation for the thermal unit commitment problem. IEEE Transactions on Power Systems 2006; 21(3): 1371-1378.
13. Baptistella LFB, Geromel JC. A decomposition approach to problem of unit commitment schedule for hydrothermal systems. Proceedings of IEEE, Vol. 149, no. 5, 1980; 250.
14. Senjyu T, Saber AY, Miyagi T, Urasaki N, Funabashi T. Absolutely stochastic simulated annealing approach to large scale unit commitment problem. Electric Power Components and Systems 2006; 34(6): 619-637.
15. Dillon JD, Walsh MP, O'Malley MJ. Initialization of the augmented Hopfield network for improved generator scheduling. IEE Proceedings Generation, Transmission and Distribution, Vol. 149, no. 5, 2002; 593-599.
16. Sheble GB, Maifeld TT. Unit commitment by genetic algorithm and expert-system. Electric Power Systems Research 1994; 30(2): 115-121.
17. Mokhtari S, Sing J, Wollenberg B. A unit commitment expert system (power system control). IEEE Transactions on Power Systems 1988; 3(1): 272-277.
18. Saneifard S, Prasad NR, Smollech HA. A fuzzy logic approach to unit commitment. IEEE Transactions on Power Systems 1997; 12(2): 988-995. (Pubitemid 127771469)
19. Kazarlis SA, Bakirtzis AG, Petridis V. A genetic algorithm solution to the unit commitment problem. IEEE Transactions on Power Systems 1996; 11: 29-36.
20. Xing W, Wu FF. Genetic algorithm based unit commitment with energy contracts. Electrical Power and Energy Systems 2002; 24: 329-336.
21. Swarup KS, Yamashiro S. A genetic algorithm approach to generator unit commitment. Electrical Power and Energy Systems 2003; 25: 679-687.
22. Yamin HY, Shabidehpour SM. Unit commitment using a hybrid model between Lagrangian relaxation and genetic algorithm in competitive electricity markets. Electric Power Systems Research 2003; 68: 83-92.
23. Zhao B, Guo CX, Bai BR, Cao YJ. An improved particle swarm optimization algorithm for unit commitment. International Journal of Electrical Power and Energy Systems 2006; 28: 482-490.
24. Damousis IG, Bakirtzis AG, Dokopoulos PS. A solution to the unit commitment problem using integer-coded genetic algorithm. IEEE Transactions on Power Systems 2004; 19(2): 1165-1172.
25. Senjyu T, Yamashiro H, Uezato K, Funabashi T. A unit commitment problem by using genetic algorithm based on unit characteristic classification. Proceedings of IEEE Power Engineering Society Winter Meeting, Vol. 1, 2002; 58-63.
26. Cheng CP, Liu CW, Liu GC. Unit commitment by Lagrangian relaxation and genetic algorithms. IEEE Transactions on Power Systems 2000; 15: 707-714.
27. Dang C, Li M. A floating-point genetic algorithm for solving the unit commitment problem. European Journal of Operational Research 2006; 1370-1395. Available online at: http://www.sciencedirect.com/(in press).
28. Goldberg DE. Genetic Algorithms in Search Optimization and Machine Learning. Addison-Wesley: Reading, MA, 1989.
29. Ling SH, Leung FHF. Real-coded genetic algorithm with average-bound crossover and wavelet mutation for network parameters learning. Proceedings of International Joint Conference on Neural Networks, Montreal, Canada, 2005; 1325-1330.
30. Sun L, Zhang Y, Jiang C. A matrix real-coded genetic algorithm to the unit commitment problem. Electric Power Systems Research 2006; 76: 716-728.
31. Juste KA, Kitu H, Tunaka E, Hasegawa J. An evolutionary programming solution to the unit commitment problem. IEEE Transactions on Power Systems 1999; 14(4): 1452-1459.
32. Srinivasan D, Chazelas J. A priority list-based evolutionary algorithm to solve large scale unit commitment problem. Proceedings of International Conference on Power System Technology, 2004; 1746-1751.
33. Ting TO, Rao MVC, Loo CK. A novel approach for unit commitment problem via an effective hybrid particle swarm optimization. IEEE Transactions on Power Systems 2006; 21(1): 411-418.
34. Gaing Z. Discrete particle swarm optimization algorithm for unit commitment. Proceedings of IEEE Power Engineering Society General Meeting, 2003; 418- 424.
35. Balci HH, Valenzuela JF. Scheduling electric power generators using particle swarm optimization combined with the Lagrangian relaxation method. International Journal of Applied Mathematics and Computer Science 2004; 14(3): 411-421.
36. Sum-im T, Ongsakul W. Ant colony search algorithm for unit commitment. Proceedings of IEEE International Conference on Industrial Technology, 2003; 72- 77.
37. Victoire TAA, Jeyakumar AE. Unit commitment by a tabusearch-based hybrid-optimisation technique. IET Proceedings Generation, Transmission and Distribution 2005; 152(4): 563-574.
38. Valenzuela J, Smith AE. A seeded memetic algorithm for large unit commitment problems. Journal of Heuristic 2002; 8: 173-195.