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    Surrogate-Based Multiperiod, Multiobjective Reservoir Operation Optimization for Quality and Quantity Management

    Source: Journal of Water Resources Planning and Management:;2020:;Volume ( 146 ):;issue: 008
    Author:
    Motahareh Saadatpour
    ,
    Abbas Afshar
    ,
    Samuel Sandoval Solis
    DOI: 10.1061/(ASCE)WR.1943-5452.0001252
    Publisher: ASCE
    Abstract: Deriving optimal reservoir operation rules in a selective withdrawal framework (SWF) considering quality and quantity objectives is a challenging problem due to its computational burdens. To overcome the computational bottleneck, two surrogate models have been developed and coupled with the evolutionary algorithm in an adaptive-recursive framework to form the surrogate-based multiobjective optimization technique (SBMOOT). SBMOOT is used to derive the optimal reservoir operating strategies and the set of nondominated optimal solutions to enhance reservoir outflow water quality and maximize water supply and hydropower energy generation. The most desirable scenarios of the Pareto front have been identified to derive monthly operating rules in the SWF. The operating rules focusing on water supply, hydropower energy, and water quality objectives are estimated using polynomial regression technique. The performances of the operating rules, with and without regarding the uncertainty of inflows, have been compared with the historical operating strategy in Karkheh Reservoir, Khuzestan, Iran. The results show that water quality measure may be enhanced while maintaining desirable water supply and/or hydropower energy compared with the historical operating strategy of Karkheh Reservoir.
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      Surrogate-Based Multiperiod, Multiobjective Reservoir Operation Optimization for Quality and Quantity Management

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4267889
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    • Journal of Water Resources Planning and Management

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    contributor authorMotahareh Saadatpour
    contributor authorAbbas Afshar
    contributor authorSamuel Sandoval Solis
    date accessioned2022-01-30T21:15:27Z
    date available2022-01-30T21:15:27Z
    date issued8/1/2020 12:00:00 AM
    identifier other%28ASCE%29WR.1943-5452.0001252.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4267889
    description abstractDeriving optimal reservoir operation rules in a selective withdrawal framework (SWF) considering quality and quantity objectives is a challenging problem due to its computational burdens. To overcome the computational bottleneck, two surrogate models have been developed and coupled with the evolutionary algorithm in an adaptive-recursive framework to form the surrogate-based multiobjective optimization technique (SBMOOT). SBMOOT is used to derive the optimal reservoir operating strategies and the set of nondominated optimal solutions to enhance reservoir outflow water quality and maximize water supply and hydropower energy generation. The most desirable scenarios of the Pareto front have been identified to derive monthly operating rules in the SWF. The operating rules focusing on water supply, hydropower energy, and water quality objectives are estimated using polynomial regression technique. The performances of the operating rules, with and without regarding the uncertainty of inflows, have been compared with the historical operating strategy in Karkheh Reservoir, Khuzestan, Iran. The results show that water quality measure may be enhanced while maintaining desirable water supply and/or hydropower energy compared with the historical operating strategy of Karkheh Reservoir.
    publisherASCE
    titleSurrogate-Based Multiperiod, Multiobjective Reservoir Operation Optimization for Quality and Quantity Management
    typeJournal Paper
    journal volume146
    journal issue8
    journal titleJournal of Water Resources Planning and Management
    identifier doi10.1061/(ASCE)WR.1943-5452.0001252
    page12
    treeJournal of Water Resources Planning and Management:;2020:;Volume ( 146 ):;issue: 008
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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