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Modeling the operation of multireservoir systems using decomposition and stochastic dynamic programming

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  • T.W. Archibald
  • K.I.M. McKinnon
  • L.C. Thomas

Abstract

Stochastic dynamic programming models are attractive for multireservoir control problems because they allow non‐linear features to be incorporated and changes in hydrological conditions to be modeled as Markov processes. However, with the exception of the simplest cases, these models are computationally intractable because of the high dimension of the state and action spaces involved. This paper proposes a new method of determining an operating policy for a multireservoir control problem that uses stochastic dynamic programming, but is practical for systems with many reservoirs. Decomposition is first used to reduce the problem to a number of independent subproblems. Each subproblem is formulated as a low‐dimensional stochastic dynamic program and solved to determine the operating policy for one of the reservoirs in the system. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006

Suggested Citation

  • T.W. Archibald & K.I.M. McKinnon & L.C. Thomas, 2006. "Modeling the operation of multireservoir systems using decomposition and stochastic dynamic programming," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(3), pages 217-225, April.
    • Handle: RePEc:wly:navres:v:53:y:2006:i:3:p:217-225
    DOI: 10.1002/nav.20134
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    References listed on IDEAS

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    1. Reznicek, K. & Cheng, T. C. E., 1991. "Stochastic modelling of reservoir operations," European Journal of Operational Research, Elsevier, vol. 50(3), pages 235-248, February.
    2. Sharon A. Johnson & Jery R. Stedinger & Christine A. Shoemaker & Ying Li & José Alberto Tejada-Guibert, 1993. "Numerical Solution of Continuous-State Dynamic Programs Using Linear and Spline Interpolation," Operations Research, INFORMS, vol. 41(3), pages 484-500, June.
    3. Victoria C. P. Chen & David Ruppert & Christine A. Shoemaker, 1999. "Applying Experimental Design and Regression Splines to High-Dimensional Continuous-State Stochastic Dynamic Programming," Operations Research, INFORMS, vol. 47(1), pages 38-53, February.
    4. T W Archibald & C S Buchanan & K I M McKinnon & L C Thomas, 1999. "Nested Benders decomposition and dynamic programming for reservoir optimisation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(5), pages 468-479, May.
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    1. Mohammed Falah Allawi & Othman Jaafar & Mohammad Ehteram & Firdaus Mohamad Hamzah & Ahmed El-Shafie, 2018. "Synchronizing Artificial Intelligence Models for Operating the Dam and Reservoir System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3373-3389, August.

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