Hybrid Linear and Nonlinear Programming Model for Hydropower Reservoir Optimization
Publication: Journal of Water Resources Planning and Management
Volume 147, Issue 3
Abstract
Linear and nonlinear optimization models are common in hydropower reservoir modeling to aid system operators and planners. Different modeling techniques have their advantages and shortcomings. Linear optimization models are faster but less accurate, and nonlinear models are slower with better system representation. A hybrid linear and nonlinear hydropower energy reservoir optimization (HERO) model is introduced, where a hybrid optimization model sequentially solves the overall nonlinear hydropower optimization problem first with a faster-running linear programming (LP) approximation to improve an initial solution for a nonlinear programming (NLP) solution to significantly reduce NLP iterations and run time. The hybrid model is applied to six hydropower plants of California, with capacities of 13.5 to 714 MW. LP and NLP decisions are compared, and run time benchmarks of the LP, NLP, and hybrid LP-NLP models with different numbers of decision variables are presented. The hybrid model reduces the NLP run time by 79% to 88%, depending on model size, but still requires much more run time than the LP solution. For short-term operations with good inflow and energy price forecasts, where accuracy matters more and uncertainties are modest, the hybrid LP-NLP model has advantages. For long-term hydropower planning and management with many more decision variables and greater inflow uncertainty, the LP model, with its greater speed and sensitivity analysis, or stochastic models, representing some uncertainties, will often be preferred.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available in a repository online in accordance with funder data retention policies (Dogan 2019b).
Acknowledgments
This research was partially supported by the US–China Clean Energy Research Center for Water-Energy Technologies (CERC-WET), Award #DE-1A0000018. The corresponding author acknowledges Jonathan Herman for his comments on the dissertation version of this paper.
References
Afshar, A., F. B. Jemaa, and M. A. Mariño. 1990. “Optimization of hydropower plant integration in water supply system.” J. Water Resour. Plann. Manage. 116 (5): 665–675. https://doi.org/10.1061/(ASCE)0733-9496(1990)116:5(665).
Allen, R. B., and S. G. Bridgeman. 1986. “Dynamic programming in hydropower scheduling.” J. Water Resour. Plann. Manage. 112 (3): 339–353. https://doi.org/10.1061/(ASCE)0733-9496(1986)112:3(339).
Barros, M. T. L., F. T.-C. Tsai, S. Yang, J. E. G. Lopes, and W. W.-G. Yeh. 2003. “Optimization of large-scale hydropower system operations.” J. Water Resour. Plann. Manage. 129 (3): 178–188. https://doi.org/10.1061/(ASCE)0733-9496(2003)129:3(178).
Bazaraa, M. S., J. J. Jarvis, and H. D. Sherali. 2010. Linear programming and network flows. 4th ed. Hoboken, NJ: Wiley.
Chatterjee, B., R. E. Howitt, and R. J. Sexton. 1998. “The optimal joint provision of water for irrigation and hydropower.” J. Environ. Econ. Manage. 36 (3): 295–313. https://doi.org/10.1006/jeem.1998.1047.
Côté, P., and R. Leconte. 2016. “Comparison of stochastic optimization algorithms for hydropower reservoir operation with ensemble streamflow prediction.” J. Water Resour. Plann. Manage. 142 (2): 04015046. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000575.
Dogan, M. S. 2019a. “Hydropower generation optimization in the era of renewables and climate change.” Doctoral dissertation, Dept. of Civil and Environmental Engineering, Univ. of California, Davis.
Dogan, M. S. 2019b. msdogan/hydropower_model: First release of hydropower model. Accessed December 16, 2019. https://github.com/msdogan/hydropower_model.
Dogan, M. S., M. A. Fefer, J. D. Herman, Q. J. Hart, J. R. Merz, J. Medellín-Azuara, and J. R. Lund. 2018. “An open-source Python implementation of California’s hydroeconomic optimization model.” Environ. Modell. Software 108 (Jun): 8–13. https://doi.org/10.1016/j.envsoft.2018.07.002.
Grygier, J. C., and J. R. Stedinger. 1985. “Algorithms for optimizing hydropower system operation.” Water Resour. Res. 21 (1): 1–10. https://doi.org/10.1029/WR021i001p00001.
Hamlet, A. F., D. Huppert, and D. P. Lettenmaier. 2002. “Economic value of long-lead streamflow forecasts for Columbia River hydropower.” J. Water Resour. Plann. Manage. 128 (2): 91–101. https://doi.org/10.1061/(ASCE)0733-9496(2002)128:2(91).
Karimanzira, D., D. Schwanenberg, C. Allen, and S. Barton. 2016. “Short-term hydropower optimization and assessment of operational flexibility.” J. Water Resour. Plann. Manage. 142 (2): 04015048. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000577.
Li, J., Y. Zhang, C. Ji, A. Wang, and J. R. Lund. 2013. “Large-scale hydropower system optimization using dynamic programming and object-oriented programming: The case of the Northeast China power grid.” Water Sci. Technol. 68 (11): 2458. https://doi.org/10.2166/wst.2013.528.
Madani, K., M. Guégan, and C. B. Uvo. 2014. “Climate change impacts on high-elevation hydroelectricity in California.” J. Hydrol. 510 (Mar): 153–163. https://doi.org/10.1016/j.jhydrol.2013.12.001.
Madani, K., and J. R. Lund. 2009. “Modeling California’s high-elevation hydropower systems in energy units.” Water Resour. Res. 45 (9): 1–12. https://doi.org/10.1029/2008WR007206.
Mariño, M. A., and H. A. Loaiciga. 1985. “Dynamic model for multi reservoir operation.” Water Resour. Res. 21 (5): 619–630. https://doi.org/10.1029/WR021i005p00619.
Martin, Q. W. 1983. “Optimal operation of multiple reservoir systems.” J. Water Resour. Plann. Manage. 109 (1): 58–74. https://doi.org/10.1061/(ASCE)0733-9496(1983)109:1(58).
Nover, D. M., M. S. Dogan, R. Ragatz, L. Booth, J. Medellín-Azuara, J. R. Lund, and J. H. Viers. 2019. “Does more storage give California more water?” J. Am. Water Resour. Assoc. 55 (3): 759–771. https://doi.org/10.1111/1752-1688.12745.
Pérez-Díaz, J. I., and J. R. Wilhelmi. 2010. “Assessment of the economic impact of environmental constraints on short-term hydropower plant operation.” Energy Policy 38 (12): 7960–7970. https://doi.org/10.1016/j.enpol.2010.09.020.
Rheinheimer, D. E., R. C. Bales, C. A. Oroza, J. R. Lund, and J. H. Viers. 2016. “Valuing year-to-go hydrologic forecast improvements for a peaking hydropower system in the Sierra Nevada.” Water Resour. Res. 52 (5): 3815–3828. https://doi.org/10.1002/2015WR018295.
Tejada-Guibert, J. A., J. R. Stedinger, and K. Staschus. 1990. “Optimization of value of CVP’s hydropower production.” J. Water Resour. Plann. Manage. 116 (1): 52–70. https://doi.org/10.1061/(ASCE)0733-9496(1990)116:1(52).
van Do, T., and C. D. D. Howard. 1988. “Hydropower stochastic forecasting and optimization.” In Proc., 3rd ASCE Water Resources Operations Management Workshop: Computerized Decision Support Systems for Water Managers, edited by J. W. Labadie, L. E. Brazil, I. Corbu, and L. E. Johnson. New York: ASCE.
Vicuña, S., J. A. Dracup, and L. Dale. 2011. “Climate change impacts on two high-elevation hydropower systems in California.” Clim. Change 109 (1): 151–169. https://doi.org/10.1007/s10584-011-0301-8.
Zhao, T., J. Zhao, and D. Yang. 2012. “Improved dynamic programming for hydropower reservoir operation.” J. Water Resour. Plann. Manage. 140 (3): 365–374. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000343.
Zhou, L., C. Cheng, S. Liao, and J. Wang. 2020. “Multiobjective scheduling method for short-term peak shaving operation of cascade hydro plants.” J. Water Resour. Plann. Manage. 146 (9): 04020073. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001274.
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Received: Mar 12, 2020
Accepted: Oct 22, 2020
Published online: Jan 8, 2021
Published in print: Mar 1, 2021
Discussion open until: Jun 8, 2021
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