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    Quarter-Hourly Operation of Large-Scale Hydropower Reservoir Systems with Prioritized Constraints

    Source: Journal of Water Resources Planning and Management:;2015:;Volume ( 141 ):;issue: 001
    Author:
    Jinwen Wang
    ,
    Shuangquan Liu
    ,
    Yongchuan Zhang
    DOI: 10.1061/(ASCE)WR.1943-5452.0000437
    Publisher: American Society of Civil Engineers
    Abstract: This paper deals with the optimization of short-term hydropower scheduling when a mathematically feasible solution cannot be achieved. Generally, the numerical search procedure terminates with the detection of infeasibility when an optimization problem is being solved. More often, however, operators of hydropower reservoirs prefer violating the mathematical constraints in order of priority, such that a satisfactory solution to the real-world problem can always be guaranteed. Previous studies rarely addressed this issue in relation to short-term operations of hydropower reservoirs. The present study relaxes the prioritized constraints with extra variables and solves the model by weighted goal programming. The weights are designed such that solving the problem is equivalent to a lexicographical optimization. The solution procedure is also efficient in dealing with large-scale problems using the following techniques: temporal and spatial decomposition of the hydro system, separate solution of plant-based operating zones, and linear programming with nonlinear local searching. The temporal decomposition has a significant advantage in computing time. An iterative procedure that converges fast is proposed to eliminate linearization errors. The model and procedure are applied to deal with the Yunnan provincial hydropower system, which consists of 44 reservoirs, believed to be one of the largest scale problems ever reported.
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      Quarter-Hourly Operation of Large-Scale Hydropower Reservoir Systems with Prioritized Constraints

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    contributor authorJinwen Wang
    contributor authorShuangquan Liu
    contributor authorYongchuan Zhang
    date accessioned2017-05-08T22:08:25Z
    date available2017-05-08T22:08:25Z
    date copyrightJanuary 2015
    date issued2015
    identifier other32318256.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/72139
    description abstractThis paper deals with the optimization of short-term hydropower scheduling when a mathematically feasible solution cannot be achieved. Generally, the numerical search procedure terminates with the detection of infeasibility when an optimization problem is being solved. More often, however, operators of hydropower reservoirs prefer violating the mathematical constraints in order of priority, such that a satisfactory solution to the real-world problem can always be guaranteed. Previous studies rarely addressed this issue in relation to short-term operations of hydropower reservoirs. The present study relaxes the prioritized constraints with extra variables and solves the model by weighted goal programming. The weights are designed such that solving the problem is equivalent to a lexicographical optimization. The solution procedure is also efficient in dealing with large-scale problems using the following techniques: temporal and spatial decomposition of the hydro system, separate solution of plant-based operating zones, and linear programming with nonlinear local searching. The temporal decomposition has a significant advantage in computing time. An iterative procedure that converges fast is proposed to eliminate linearization errors. The model and procedure are applied to deal with the Yunnan provincial hydropower system, which consists of 44 reservoirs, believed to be one of the largest scale problems ever reported.
    publisherAmerican Society of Civil Engineers
    titleQuarter-Hourly Operation of Large-Scale Hydropower Reservoir Systems with Prioritized Constraints
    typeJournal Paper
    journal volume141
    journal issue1
    journal titleJournal of Water Resources Planning and Management
    identifier doi10.1061/(ASCE)WR.1943-5452.0000437
    treeJournal of Water Resources Planning and Management:;2015:;Volume ( 141 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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