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Many-Objective Multi-Scenario Algorithm for Optimal Reservoir Operation Under Future Uncertainties

Author

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  • Farzane Karami

    (KN Toosi University of Technology)

  • Alireza B. Dariane

    (KN Toosi University of Technology)

Abstract

An increase in greenhouse gases in future can exacerbate the climate change phenomenon and may have negative consequences on different elements of hydrologic system, including rainfall, temperature, and streamflow. Since the reservoir operation is highly dependent on the timing and magnitude of inflow, the impact of potential climate change on inflow sequences should be considered in deriving the system operation rule. Nevertheless, existing algorithms are only able to optimize the operation policy for a single predetermined climate scenario. Thus, the derived operation rule would not work well if the scenario changes. This paper proposes an algorithm which is able to handle simultaneously multiple scenarios in finding optimum system operation rule. Thus, it can overcome drawbacks caused by uncertainties in the occurrence of future scenarios. The proposed algorithm is used to optimize reservoir operation policy considering various climate change scenarios (RCPs). To evaluate the performance of the proposed algorithm, a five-reservoir system within Tehran region with several objectives including municipal, agricultural, environmental, and hydropower demands is employed as the case study. Results show that in all cases the multi-scenario rule derived by the proposed method performs as good as the operation rule derived for any specific scenario using a powerful optimization algorithm when evaluated for that scenario. While, in all other models as the future scenario changes to the one other than that used in deriving the operation rule, the model performance declines as compared to the proposed model.

Suggested Citation

  • Farzane Karami & Alireza B. Dariane, 2018. "Many-Objective Multi-Scenario Algorithm for Optimal Reservoir Operation Under Future Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(12), pages 3887-3902, September.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:12:d:10.1007_s11269-018-2025-2
    DOI: 10.1007/s11269-018-2025-2
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    Cited by:

    1. Dariane, A.B. & Ghasemi, M. & Karami, F. & Azaranfar, A. & Hatami, S., 2021. "Crop pattern optimization in a multi-reservoir system by combining many-objective and social choice methods," Agricultural Water Management, Elsevier, vol. 257(C).
    2. Wei Zhang & Xiaohui Lei & Pan Liu & Xu Wang & Hao Wang & Peibing Song, 2019. "Identifying the Relationship between Assignments of Scenario Weights and their Positions in the Derivation of Reservoir Operating Rules under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 261-279, January.
    3. A. B. Dariane & E. Pouryafar, 2021. "Quantifying and projection of the relative impacts of climate change and direct human activities on streamflow fluctuations," Climatic Change, Springer, vol. 165(1), pages 1-20, March.
    4. Guerra, Omar J. & Tejada, Diego A. & Reklaitis, Gintaras V., 2019. "Climate change impacts and adaptation strategies for a hydro-dominated power system via stochastic optimization," Applied Energy, Elsevier, vol. 233, pages 584-598.

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