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Multistage scenario-based interval-stochastic programming for planning water resources allocation

机译:基于多阶段情景的区间随机规划的水资源分配规划

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摘要

In this study, a multistage scenario-based interval-stochastic programming (MSISP) method is developed for water-resources allocation under uncertainty. MSISP improves upon the existing multistage optimization methods with advantages in uncertainty reflection, dynamics facilitation, and risk analysis. It can directly handle uncertainties presented as both interval numbers and probability distributions, and can support the assessment of the reliability of satisfying (or the risk of violating) system constraints within a multistage context. It can also reflect the dynamics of system uncertainties and decision processes under a representative set of scenarios. The developed MSISP method is then applied to a case of water resources management planning within a multi-reservoir system associated with joint probabilities. A range of violation levels for capacity and environment constraints are analyzed under uncertainty. Solutions associated different risk levels of constraint violation have been obtained. They can be used for generating decision alternatives and thus help water managers to identify desired policies under various economic, environmental and system-reliability conditions. Besides, sensitivity analyses demonstrate that the violation of the environmental constraint has a significant effect on the system benefit.
机译:在这项研究中,开发了一种基于多阶段情景的区间随机规划(MSISP)方法来确定不确定性下的水资源。 MSISP对现有的多阶段优化方法进行了改进,在不确定性反映,动力学简化和风险分析方面具有优势。它可以直接处理表示为区间数和概率分布的不确定性,并且可以支持评估多阶段上下文中满足(或违反风险)系统约束的可靠性。它也可以反映一组代表性场景下系统不确定性和决策过程的动态。然后,将开发的MSISP方法应用于与联合概率相关的多水库系统内的水资源管理计划。在不确定性下分析了一系列针对容量和环境约束的违规级别。已获得与约束违反的不同风险级别相关的解决方案。它们可用于生成决策选择方案,从而帮助水管理人员在各种经济,环境和系统可靠性条件下确定所需的政策。此外,敏感性分析表明,违反环境约束对系统效益具有重大影响。

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