Fast multireservoir multiperiod linear programing models
Fast multireservoir multiperiod linear programing models
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快速多储层多周期线性规划模型
DOI：
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发表时间：
1989
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通讯作者：
G. Kuczera
中科院分区：
文献类型：
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作者：
G. Kuczera
多储层、多周期线性规划模型通常计算成本非常昂贵。其中一些模型可以表述为网络线性程序 (NLP)，计算机编码速度比一般线性编程代码快约 100 倍。提出了一种 NLP 公式，用于确定多水库系统在某个时间范围内的水分配。它提供了由于干旱或调水限制而导致的需求区短缺、干旱期间可能违反的河道流量要求以及季节性水库目标容量。它还允许探索可靠性和需求短缺严重程度之间的权衡。案例研究说明了计算性能。针对 324 个周期建模的三水库、两需求区供水系统制定了 NLP。在 VAX 8550 计算机上，该问题在 26 CPU 秒内得到解决。最后，结果表明，可以制定自然语言处理来找到多水库系统中一个水库所需的最小容量，从而在某个规划期内恰好满足系统需求。
Multireservoir, multiperiod linear programing models are typically computationally very expensive. Some of these models can be formulated as network linear programs (NLPs), for which computer codes about 100 times faster than general linear programing codes are available. A NLP formulation is presented for determining water assignments in a multireservoir system over some time horizon. It provides for demand zone shortfalls due to drought or transfer limitations, instream flow requirements, which can be violated during droughts, and seasonal reservoir target volumes. It also allows the trade-off between reliability and demand shortfall severity to be explored. A case study illustrates computational performance. A NLP was formulated for a three-reservoir, two-demand zone water supply system modeled over 324 periods. It was solved in 26 CPU seconds on a VAX 8550 computer. Finally, it is shown that a NLP can be formulated to find the required minimum capacity of one reservoir in a multireservoir system so that system demand is just meet over some planning period.