Reservoir operation using a robust evolutionary optimization algorithm.
In this research, a significant improvement in reservoir operation was achieved using a state-of-the-art evolutionary algorithm named Borg MOEA. A real-world multipurpose dam was used to test the algorithm's performance, and the target of the reservoir operation policy was to fulfil downstream water...
| Publicado en: | Journal of Environmental Management Vol. 197; pp. 275 - 287 |
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| Autores principales: | , |
| Formato: | Artículo |
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Academic Press Inc.
Jul2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=122826933&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 122826933 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03014797 EMJ jtl: Journal of Environmental Management issn: 03014797 maglogo: N pubinfo: dt: Jul2017 vid: 197 pid: 735 pub: Academic Press Inc. artinfo: ui: 122826933 10.1016/j.jenvman.2017.03.081 ppf: 275 ppct: 12 formats: tig: atl: Reservoir operation using a robust evolutionary optimization algorithm. aug: au: Al-Jawad, Jafar Y. Tanyimboh, Tiku T. affil: Department of Civil and Environmental Engineering, University of Strathclyde Glasgow, 75 Montrose St, Glasgow G1 1XJ, UK su: Water supply Reservoir drawdown Robust optimization Water management Water storage sug: subj: Water supply Water Supply and Irrigation Systems Reservoir drawdown Robust optimization Water management Water storage keyword: Environmental water management Evolutionary optimization algorithm Multipurpose reservoir system Reservoir drawdown limits Reservoir operation policy Self-adaptive recombination Environmental water management Evolutionary optimization algorithm Multipurpose reservoir system Reservoir drawdown limits Reservoir operation policy Self-adaptive recombination ab: In this research, a significant improvement in reservoir operation was achieved using a state-of-the-art evolutionary algorithm named Borg MOEA. A real-world multipurpose dam was used to test the algorithm's performance, and the target of the reservoir operation policy was to fulfil downstream water demands in drought condition while maintaining a sustainable quantity of water in the reservoir for the next year. The reservoir's performance was improved by increasing the maximum reservoir storage by 14.83 million m 3 . Furthermore, sustainable water storage in the reservoir was achieved for the next year, for the simulated low flow condition considered, while the total annual imbalance between the monthly reservoir releases and water demands was reduced by 64.7%. The algorithm converged quickly and reliably, and consistently good results were obtained. The methodology and results will be useful to decision makers and water managers for setting the policy to manage the reservoir efficiently and sustainably. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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