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Inexact Two-Stage Stochastic Programming for Water Resources Allocation under Considering Demand Uncertainties and Response—A Case Study of Tianjin, China

机译:考虑需求不确定性和响应的水资源分配的不精确两阶段随机规划-以天津为例

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In this paper, an inexact two-stage stochastic programming model was developed for supporting regional water resource allocation management under uncertainties. The proposed model is an integrated framework of interval parameter programming and two-stage stochastic programming, which can tackle uncertain parameters expressed as interval values with probability distribution information. The proposed model was successfully applied to a typical heavy industrial city suffering water shortage in the east of China, Tianjin. The uncertainties of future water demand were taken into account through generating a set of representative scenarios. The results indicated that different scenarios would affect the water distribution patterns, water shortages, total benefits and system cost. The results revealed that the transferred water from Luan River and Changjiang River would still be the main water resource for each water user. Besides, nearly all water demand in planning horizon would be guaranteed through the reasonable dispatch except under high demand level scenario, in which a small proportion of water requirement in agricultural, municipal and environmental sectors would not be satisfied. The developed method could be used by environmental managers to identify the optimal water supply plan from multiple sources to different end-user sectors under system uncertainties.
机译:本文建立了一个不精确的两阶段随机规划模型来支持不确定性下的区域水资源分配管理。所提出的模型是区间参数规划和两阶段随机规划的集成框架,可以解决带有概率分布信息的区间参数表示的不确定参数。所提出的模型已成功地应用于中国东部城市天津缺水的典型重工业城市。通过生成一组具有代表性的方案,考虑了未来用水需求的不确定性。结果表明,不同的情景将影响配水方式,缺水,总收益和系统成本。结果表明,Lu河和长江调水仍将是每个用水户的主要水资源。此外,除了在高需求水平的情况下,几乎无法满足规划范围内几乎所有的用水需求,在高需求水平的情况下,农业,市政和环境部门的用水需求都无法满足。环境管理员可以使用这种开发的方法来确定系统不确定性下从多个来源到不同最终用户部门的最佳供水计划。

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