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A stochastic approach to analyze trade-offs and risks associated with large-scale water resources systems

机译:一种分析大型水资源系统相关权衡和风险的随机方法

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Water resources development projects often involve multiple and conflicting objectives as well as stochastic hydrologic inputs. Multiobjective optimization techniques can be used to identify noninferior solutions and to construct a trade-off relationship between conflicting objectives. This paper presents a methodology for analyzing trade-offs and risks associated with large-scale water resource projects under hydrologic uncertainty. The proposed methodology relies on the stochastic dual dynamic programming (SDDP) model to derive monthly or weekly operating rules for multipurpose multireservoir systems taking into account the stochasticity of the inflows, irrigation water withdrawals, minimum/maximum flow requirements for navigation, fishing, and/or for ecological purposes. In SDDP, release decisions are chosen so as to minimize the operating costs of a hydrothermal electrical system. Irrigation water demands and other operating constraints are imposed on the system through the SDDP model. The proposed methodology is illustrated with the Southeastern Anatolia Development project, commonly called GAP, in Turkey. The GAP is a multidimensional-development project involving primarily the production of hydroelectricity and irrigation. Simulation results using 50 hydrologic scenarios show that the complete development of the irrigation projects would reduce the total energy output by 6.5% and will increase the risk of not meeting minimum outflow at the Syrian border from 5% to 25%.
机译:水资源开发项目通常涉及多个相互矛盾的目标以及随机的水文投入。多目标优化技术可用于识别非劣等解并在冲突目标之间建立折衷关系。本文提出了一种在水文不确定性下分析与大型水资源项目相关的权衡和风险的方法。拟议的方法基于随机双重动态规划(SDDP)模型来得出多用途多水库系统的每月或每周运行规则,并考虑到流入量的随机性,灌溉用水取水量,航行,垂钓和/或最低/最高流量要求或出于生态目的。在SDDP中,选择释放决策以使水热电气系统的运行成本最小化。通过SDDP模型将灌溉水需求和其他操作限制强加给系统。土耳其的东南安纳托利亚开发项目(通常称为GAP)说明了所建议的方法。 GAP是一个多维开发项目,主要涉及水力发电和灌溉。使用50种水文情景的模拟结果表明,灌溉项目的全面发展将使总能源输出减少6.5%,并将无法满足叙利亚边界最低流出量的风险从5%提高到25%。

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