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Reliability Improved Stochastic Dynamic Programming for Reservoir Operation Optimization

Author

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  • Mohsen Saadat

    (Isfahan University of Technology)

  • Keyvan Asghari

    (Isfahan University of Technology)

Abstract

Stochastic Dynamic Programming (SDP) is widely used in reservoir operation problems. Besides its advantages, a few drawbacks have leaded many studies to improve its structure. Handling the infeasible conditions and curse of dimensionality are two major challenges in this method. The main goal of this paper is proposing a new method to avoid infeasible conditions and enhance the solution efficiency with new discretization procedure. For this purpose, an optimization module is incorporated into regular SDP structure, so that, near optimal values of state variables are determined based on the available constraints. The new method (RISDP) employs reliability concept to maximize the reservoir releases to satisfy the downstream demands. Applying the proposed technique improves the reservoir operating policies compared to regular SDP policies with the same assumptions of discretization. Simulation of reservoir operation in a real case study indicates about 15% improvement in objective function value and elimination of infeasible conditions by using RISDP operating policies.

Suggested Citation

  • Mohsen Saadat & Keyvan Asghari, 2017. "Reliability Improved Stochastic Dynamic Programming for Reservoir Operation Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(6), pages 1795-1807, April.
    • Handle: RePEc:spr:waterr:v:31:y:2017:i:6:d:10.1007_s11269-017-1612-y
    DOI: 10.1007/s11269-017-1612-y
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    References listed on IDEAS

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    2. Sabah Fayaed & Ahmed El-Shafie & Othman Jaafar, 2013. "Integrated Artificial Neural Network (ANN) and Stochastic Dynamic Programming (SDP) Model for Optimal Release Policy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(10), pages 3679-3696, August.
    3. Abbas Afshar & Fariborz Masoumi & Sam Solis, 2015. "Reliability Based Optimum Reservoir Design by Hybrid ACO-LP Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 2045-2058, April.
    4. Deepti Rani & Maria Moreira, 2010. "Simulation–Optimization Modeling: A Survey and Potential Application in Reservoir Systems Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(6), pages 1107-1138, April.
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    Cited by:

    1. Deji Baima & Guoyuan Qian & Jingzhen Luo & Pengcheng Wang & Hao Zheng & Jinwen Wang, 2024. "Monthly Hydropower Scheduling of Cascaded Reservoirs Using a Genetic Algorithm with a Simulation Procedure," Energies, MDPI, vol. 17(15), pages 1-17, July.
    2. Feng, Zhong-kai & Huang, Qing-qing & Niu, Wen-jing & Su, Hua-ying & Li, Shu-shan & Wu, Hui-jun & Wang, Jia-yang, 2024. "Peak operation optimization of cascade hydropower reservoirs and solar power plants considering output forecasting uncertainty," Applied Energy, Elsevier, vol. 358(C).
    3. Aadhityaa Mohanavelu & Bankaru-Swamy Soundharajan & Ozgur Kisi, 2022. "Modeling Multi-objective Pareto-optimal Reservoir Operation Policies Using State-of-the-art Modeling Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3107-3128, July.
    4. Mengfei Xie & Suzhen Feng & Jinwen Wang & Maolin Zhang & Cheng Chen, 2022. "Impacts of Yield and Seasonal Prices on the Operation of Lancang Cascaded Reservoirs," Energies, MDPI, vol. 15(9), pages 1-11, April.

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