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  • 1
    Online-Ressource
    Online-Ressource
    Elsevier BV ; 2019
    In:  Computational and Structural Biotechnology Journal Vol. 17 ( 2019), p. 430-440
    In: Computational and Structural Biotechnology Journal, Elsevier BV, Vol. 17 ( 2019), p. 430-440
    Materialart: Online-Ressource
    ISSN: 2001-0370
    Sprache: Englisch
    Verlag: Elsevier BV
    Publikationsdatum: 2019
    ZDB Id: 2694435-2
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 2
    Online-Ressource
    Online-Ressource
    IWA Publishing ; 2021
    In:  Water Supply Vol. 21, No. 7 ( 2021-11-01), p. 3330-3343
    In: Water Supply, IWA Publishing, Vol. 21, No. 7 ( 2021-11-01), p. 3330-3343
    Kurzfassung: An optimal flood-limiting water level (FLWL) is needed to solve the contradiction between flood control safety measures and utilizable benefits. Therefore, this paper took the Chengbi River reservoir as an example, applied the Monte Carlo stochastic simulation and water consumption rate per unit of electrical energy methods to calculate the flood control risks and benefits associated with raising the FLWL in stages, and used the fuzzy comprehensive evaluation method to select the optimal FLWL for each stage of the flood season, which provided a scientific basis for the effective use of rainfall and flood data in the reservoir. The major outcomes of the study are as follows. (1) The reservoir flood season can be divided into a preflood season (April to May), a main flood season (June to August), and a later flood season (September to October). (2) The flood risks and power generation benefits of the reservoir are calculated after raising the FLWL, the optimal FLWL for the main flood season is 185.5 m, and the optimal FLWL for the later flood season is 187.50 m, while the FLWL in the preflood season should be kept at 185.0 m. The above results can provide scientific support for flood control safety planning and the optimal operation of reservoirs.
    Materialart: Online-Ressource
    ISSN: 1606-9749 , 1607-0798
    RVK:
    Sprache: Englisch
    Verlag: IWA Publishing
    Publikationsdatum: 2021
    ZDB Id: 2967640-X
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 3
    In: Water, MDPI AG, Vol. 14, No. 4 ( 2022-02-16), p. 608-
    Kurzfassung: In order to solve the problem that the existing optimal operation model of reservoirs cannot coordinate the contradiction between long-term and short-term benefits, the paper nested the long-term optimal operation and mid-long-term optimal operations of reservoirs and established the multi-objective optimal operation nested model of reservoirs. At the same time, based on this model, the optimal control mode is determined when there are errors in the predicted runoff. In the optimal scheduling nested model, the dynamic programming algorithm is used to determine the long-term optimal scheduling solution, and the genetic algorithm is used to solve the mid-long-term optimal scheduling. The optimal control mode is determined by three indicators: power generation benefit, water level over limit risk rate and the not-exploited water volume. The results show that, on the premise of meeting the flood control objectives, the nested model optimal dispatching plan has higher benefits than the long-term optimal dispatching plan and the actual dispatching plan, which verifies the superiority of the nested model in the reservoir optimal dispatching problem. When there is error in predicting runoff, among the water level control mode, flow control mode and output control mode, the average power generation benefit of output control mode is 150.05 GW·h, the low-risk rate of water level overrun is 0.29, and the not-exploited water volume is 39,270 m3. Compared with the water level control mode and the flow control mode, the output control mode has the advantages of higher power generation efficiency, lower water level over limit risk rate and less not-exploited water volume. Therefore, from the perspective of economic benefit and risk balance, the output control mode in the optimization scheduling nested mode is the optimal control mode.
    Materialart: Online-Ressource
    ISSN: 2073-4441
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2022
    ZDB Id: 2521238-2
    Standort Signatur Einschränkungen Verfügbarkeit
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