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首页> 外文期刊>Journal of Water Resources Planning and Management >Least-cost design of water distribution networks under demand uncertainty
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Least-cost design of water distribution networks under demand uncertainty

机译：需求不确定性下的配水网最低成本设计

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摘要

Due to inherent variability in instantaneous water consumption levels, values of demands at nodes in a water distribution system remain one of the major sources of uncertainty in the network design process. Uncertainty in demand leads to uncertainty in head at the nodes, which, in turn, affects the system performance and has to be taken into account when designing new water distribution systems or extending/rehabilitating existing ones. One approach to dealing with this difficulty is to formulate and solve the stochastic optimization problem providing a robust, cost-effective solution. However, stochastic formulation usually requires Monte Carlo simulation, which involves calculation of a large number of state estimates, even for relatively simple networks. This renders the approach intractable when combined with heuristic adaptive search techniques, such as genetic algorithms (GAs) or simulated annealing. These methodologies require the fitness function to be evaluated for thousands of possible network configurations in the course of the search process. In this paper a new approach to quantifying the influence of demand uncertainty on nodal heads is proposed. The original stochastic model is reformulated as a deterministic one, which uses standard deviation as a natural measure of variability. Such an approach allows the use of effective numerical methods to quantify the influence of uncertainty on the robustness of water distribution system solutions. The deterministic equivalent is then coupled with an efficient GA solver to find robust and economic solutions. The proposed methodology was tested on the New York tunnels and Anytown problems. A number of low cost network solutions were found for different levels of reliability and different forms of probability distribution function for demands. The robustness of the solutions found was compared to known solutions for deterministic formulations, whose results were postprocessed using full Monte Carlo simulation.
机译：由于瞬时用水量的内在变化，配水系统中节点的需求值仍然是网络设计过程中不确定性的主要来源之一。需求的不确定性会导致节点处水头的不确定性，进而影响系统性能，在设计新的供水系统或扩展/修复现有供水系统时必须考虑到这一点。解决此难题的一种方法是制定和解决随机优化问题，从而提供可靠，经济高效的解决方案。但是，随机表述通常需要蒙特卡洛模拟，即使对于相对简单的网络，也需要计算大量状态估计。当与启发式自适应搜索技术（例如遗传算法（GA）或模拟退火）结合使用时，这种方法难以处理。这些方法要求在搜索过程中针对数千种可能的网络配置评估适应度函数。本文提出了一种量化需求不确定性对节点头影响的新方法。原始随机模型被重新构造为确定性模型，该模型使用标准差作为变异性的自然度量。这种方法允许使用有效的数值方法来量化不确定性对配水系统解决方案鲁棒性的影响。然后，确定性等效项与有效的GA求解器结合使用，以找到可靠且经济的解决方案。在纽约隧道和Anytown问题上测试了所提出的方法。人们发现了许多低成本网络解决方案，它们具有不同的可靠性水平和不同形式的需求概率分布函数。将找到的解决方案的鲁棒性与确定性公式的已知解决方案进行比较，确定性公式的结果使用完整的蒙特卡洛模拟进行了后处理。

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