Optimal Dispatching Model Considering the Pumped Sto-rage Power Plant in Hunan

Xinfan Jiang, Dunnan Liu, Siyuan Zhang, Wenlei Zhang

Dispatching Control Center, Hunan Electric Power Company, Changsha, China.
School of Economics and Management, North China Electric Power University.

DOI: 10.4236/epe.2013.54B117                

Abstract

This paper made a research on the Intelligent Optimization Operating Modeling of Pumped Storage Power Station in Hunan Power Grid. First it introduces the characteristics of Hunan power grid and analysis the practical requirement of dispatching. Then it brings forward the intelligent optimization model and set up running model for pumped storage power station of Hei Mi-feng. At last, it introduces the application of pumped storage power station in Hunan power grid and proves the effectiveness of the optimization models.

Keywords

Intelligent Optimization; Dispatching Model; Pumped Storage Power Station

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	W. Y. Qian, Y. G. Dang, S. Mu and X. M. Li, “The IntelLigent Optimization of GM(1,1) Power Model and Its Application in the Forecast of Traffic Accident,” Proceedings of 2011 IEEE International Conference on Grey Systems and Intelligent Services, GSIS'11 - Joint with the 15th WOSC International Congress on Cybernetics and Systems, 2011, pp. 385-389.
[2]	Z. Y. Bi, Q. F. Wang and J. Z. Tang, “Working Point’s On-line Intelligent Optimization Strategy for Dredging Slurry Pipeline Transportation,” Proceedings of the World Congress on Intelligent Control and Automation (WCICA), 2008, pp. 9083-9088.
[3]	N. Lu, J. H. Chow and A. A. Desrochers, “Pumped-storage Hydro-turbine Bidding Strategies in a Competitive Electricity Market,” IEEE Transactions on Power Systems, Vol. 19, No. 2, 2004, pp. 834-841. doi:10.1109/TPWRS.2004.825911
[4]	E. Ni, P. B. Luh and S. Rourke, “Optimal Integrated Generation Bidding and Scheduling with Risk Management under a Deregulated Power Market,” IEEE Transactions on Power Systems, Vol. 19, No. 1, 2004, pp. 600-609. doi:10.1109/TPWRS.2003.818695
[5]	Pehlivanoglu and Y. Volkan, “Hybrid Intelligent Optimization Methods for Engineering Problems,” Dissertation Abstracts International, 2010.