Estimating Maximal Annual Energy Given Heterogeneous Hydropower Generating Units with Application to the Three Gorges System
Publication: Journal of Water Resources Planning and Management
Volume 139, Issue 3
Abstract
A hierarchical optimization method is presented for an assessment of the potential maximum energy output of the Three Gorges Project and Gezhouba cascade hydropower stations in China. The optimization incorporates a detailed description of daily load dispatching among different types of hydropower units. The optimization method is divided into three levels to render feasible the computation of the global optimization problem. In levels 1 and 2, a genetic algorithm is applied to optimize discharge and water head distribution between the upstream and downstream reservoirs. Level 1 selects the water levels at the beginning of each month in a year. Level 2 selects the water levels at the beginning of each day in a month. Level 3 solves a linear programming problem for allocation of water among the heterogeneous types of hydropower generation. Hydrological data of the years 2004 and 2005 are used to perform an optimized power generation process within the operating rules. The maximal annual energy production could be approximately 61 and 87 MWh higher than the actual recorded energy production in 2004 and 2005, respectively.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The Three Gorges Corporation and the National Key Technology Research and Development Program No. 2008BAB29B09 and No. 2009BAC56B03 in China supported this research. A fellowship from Chinese government to visit Cornell University for one year supported Fang-Fang Li. NSF grants EAR0711491 and CBET 075675 partially supported C. A. Shoemaker.
References
Ahmed, J. A., and Sarma, A. K. (2005). “Genetic algorithm for optimal operating policy of a multipurpose reservoir.” Water Resour. Manage., 19(2), 145–161.
Arnold, E., Tatjewski, P., and Wolochowicz, P. (1994). “Two methods for large-scale nonlinear optimization and their comparison on a case study of hydropower optimization.” J. Optim. Theory Appl., 81(2), 221–248.
Brandão, J. L. B. (2010). “Performance of the equivalent reservoir modelling technique for multi-reservoir hydropower systems.” Water Resour. Manage., 24(12), 3101–3114.
Cai, X. M., McKinney, D. C., and Lasdon, L. S. (2001a). “Solving nonlinear water management models using a combined genetic algorithm and linear programming approach.” Adv. Water Resour., 24(6), 667–676.
Cai, X. M., McKinney, D. C., Lasdon, L. S., and Watkins, D. (2001b). “Solving large nonconvex water resources management models using generalized Benders decomposition.” Oper. Res., 49(2), 235–245.
Cao, G. J., Cai, Z. G., Liu, Z. W., and Wang, G. Q. (2007). “Daily optimized model for long-term operation of the Three Gorges-Gezhouba cascade power stations.” Sci. China Ser. E, 50(S1), 98–110.
Chang, J. X., Huang, Q., and Wang, Y. M. (2005). “Genetic algorithms for optimal reservoir dispatching.” Water Resour. Manage., 19(4), 321–331.
Chen, V. C. P., Ruppert, D., and Shoemaker, C. A. (1999). “Applying experimental design and regression splines to high-dimensional continuous-state stochastic dynamic programming.” Oper. Res., 47(1), 38–53.
Deb, K. (2000). “An efficient constraint handling method for genetic algorithms.” Comput. Meth. Appl. Mech. Eng., 186(2), 311–338.
Deb, K., and Agrawal, R. B. (1995). “Simulated binary crossover for continuous search space.” Complex Syst., 9(2), 115–148.
Deb, K., and Goyal, M. (1996). “A combined genetic adaptive search (gene AS) for engineering design.” Comput. Sci. Inform., 26(1), 30–45.
Diniz, A. L., Esteves, P. P. I., and Sagastizábal, C. A. (2007). “A mathematical model for the efficiency curves of hydroelectric units.” Proc., IEEE-PES General Meeting, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, N.J., 1–7.
Fontane, D. G., Gates, T. K., and Moncada, E. (1997). “Planning reservoir operations with imprecise objectives.” J. Water Resour. Plann. Manage., 123(3), 154–162.
Georgakakos, A. P., Yao, H., and Yu, Y. (1997). “Control model for hydroelectric energy-value optimization.” J. Water Resour. Plann. Manage., 123(1), 30–38.
Gil, E., Bustos, J., and Rudnick, H. (2003). “Short-term hydrothermal generation scheduling model using a genetic algorithm.” IEEE Trans. Power Syst., 18(4), 1256–1264.
Grygier, J. C., and Stedinger, J. R. (1985). “Algorithms for optimizing hydropower system operation.” Water Resour. Res., 21(1), 1–10.
Hormwichian, R., Kangrang, A., and Lamom, A. (2009). “A conditional genetic algorithm model for searching optimal reservoir rule curves.” J. Appl. Sci., 9(19), 3575–3580.
Howard, C. D. D. (2006). “Hydroelectric system operations optimization.” Great Wall World Renewable Energy Forum and Exhibition, Chinese Wind Energy Association, Beijing, China, 1–7.
Jain, S. K., Das, A., and Srivastava, D. K. (1999). “Application of ANN for reservoir inflow prediction and operation.” J. Water Resour. Plann. Manage., 125(5), 263–271.
Johnson, S. A., Stedinger, J. R., Shoemaker, C. A., Li, Y., and Tejada-Guibert, J. A. (1993). “Numerical solution of continuous-state dynamic programs using linear and spline interpolation.” Oper. Res., 41(3), 484–500.
Labadie, J. W. (2004). “Optimal operation of multireservoir systems: State-of-the-art review.” J. Water Resour. Plann. Manage., 130(2), 93–111.
Martin, Q. W. (2000). “Automated real-time hydropower scheduling for Lower Colorado River, Texas.” Proc., Watershed Management and Operations Management, ASCE, Reston, VA, 1–9.
Martin, Q. W. (1995). “Optimal reservoir control for hydropower on Colorado River, Texas.” J. Water Resour. Plann. Manage., 121(6), 438–446.
Momtahen, Sh., and Dariane, A. B. (2007). “Direct search approaches using genetic algorithms for optimization of water reservoir operating policies.” J. Water Resour. Plann. Manage., 133(3), 202–209.
Nandalal, K. D. W., and Bogardi, J. J. (2007). Dynamic programming based operation of reservoirs: Applicability and limits, Cambridge University Press, Cambridge, UK, 16–30.
Raman, H., and Chandramouli, V. (1996). “Deriving a general operating policy for reservoir using neural network.” J. Water Resour. Plann. Manage., 122(5), 342–347.
Turgeon, A., and Charbonneau, R. (1998). “An aggregation-disaggregation approach to long-term reservoir management.” Water Resour. Res., 34(12), 3585–3594.
Unver, O. I., and Mays, L. W. (1990). “Model for real-time optimal flood control operation of a reservoir system.” Water Resour. Manage., 4(1), 21–46.
Watkins,D. W., Jr., and McKinney, D. C. (1997). “Finding robust solutions to water resources problems.” J. Water Resour. Plann. Manage., 123(1), 49–58.
Wurbs, R. A. (1993). “Reservoir-system simulation and optimization models.” J. Water Resour. Plann. Manage., 119(4), 455–472.
Yeh, W. W.-G., Becker, L., Hua, S.-Q., Wen, D.-P., and Liu, D.-P. (1992). “Optimization of real-time hydrothermal system operation.” J. Water Resour. Plann. Manage., 118(6), 636–653.
Information & Authors
Information
Published In
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Mar 29, 2011
Accepted: Apr 4, 2012
Published online: Apr 11, 2012
Published in print: May 1, 2013
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.