Short term hydroelectric power system scheduling with wind turbine generators using the multi-pass iteration particle swarm optimization approach

Energy Conversion and Management

Volumn 49, Issue 4, 2008, Pages 751-760

  Lee, Tsung Ying ^a  

^a MINGHSIN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

Author keywords

Hydroelectric; Multi pass iteration particle swarm optimization; Wind turbine generators

Indexed keywords

ALGORITHMS; PARTICLE SWARM OPTIMIZATION (PSO); SCHEDULING; WIND TURBINES;

MULTI-PASS ITERATION PARTICLE SWARM OPTIMIZATION (MIPSO); WIND TURBINE GENERATORS;

HYDROELECTRIC POWER;

EID: 39749190065     PISSN: 01968904     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enconman.2007.07.019     Document Type: Article

References (16)

1. Li F, Kuri B. Generation scheduling in a system with wind power. In: 2005 IEEE/PES transmission and distribution conference and exhibition: Asia and Pacific, August 2005. p. 1-6.
2. Sinha N., Chakrabarti R., and Chattopadhyay P.K. Fast evolutionary programming techniques for short-term hydrothermal scheduling. IEEE Trans Power Syst 18 1 (2003) 214-220
3. Zoumas C.E., Bakirtzis A.G., Theocharis J.B., and Petridis V.A. A genetic algorithm solution approach to the hydrothermal coordination problem. IEEE Trans Power Syst 19 3 (2004) 1356-1364
4. Yang J.S., and Chen N. Short term hydrothermal coordination using multi-pass dynamic programming. IEEE Trans Power Syst 4 3 (1989) 1050-1056
5. Enamorado JC, Ramos A, Gomez T. Multi-area decentralized optimal hydro-thermal coordination by the Dantzig-Wolfe decomposition method. In: PES summer meeting, vol. 4; 2000. p. 2027-32.
6. Nilson O, Sjelvgren D, Mixed integer programming applied to short-term planning of a hydro-thermal system. In: Proceedings of the 1995 IEEE PICA, May 1995. p. 158-63.
7. Salam S., Nor K.M., and Hamdan A.R. Comprehensive algorithm for hydrothermal coordination. IEE Proc- Generat Transmiss Distribut 144 5 (1997) 482-488
8. Wong K.P., and Wong Y.W. Short-term hydrothermal scheduling part. I. Simulated annealing approach. IEE Proc Generat Transmiss Distribut 141 5 (1994) 497-501
9. Kennedy J, Eberhart R. Particle swarm optimization. In: Proceedings of the IEEE international conference on neural networks; 1995. p. 1942-48.
10. Kennedy J, Eberhart R. A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science; 1995. p. 39-43.
11. Chuanwen J., and Bompard E. A self-adaptive chaotic particle swarm algorithm for short term hydroelectric system scheduling in deregulated environment. Energy Convers Manage 46 17 (2005) 2689-2696
12. Cai J., Ma X., Li L., and Peng H. Chaotic particle swarm optimization for economic dispatch considering generator constraints. Energy Convers Manage 48 2 (2007) 645-653
13. Gaing ZL, Constrained dynamic economic dispatch solution using particle swarm optimization. In: IEEE power engineering society general meeting. p. 153-8.
14. Lee T.Y., and Chen C.L. Unit commitment with probabilistic reserve: an ipso approach. Energy Conver Manag 48 2 (2007) 486-493
15. National Renewable Energy Laboratory, US, HOMER the optimization model for distributed power-getting started guide v2.0, May 2003.
16. Salameh Z.M., and Safari I. Optimum windmill-site matching. IEEE Trans Energy Convers 7 4 (1992) 669-676