Impact analysis of stochastic inflow prediction with reliability and discrimination indices on long-term reservoir operation
Impact analysis of stochastic inflow prediction with reliability and discrimination indices on long-term reservoir operation
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DOI：
10.2166/hydro.2013.206
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发表时间：
2014-01-01
影响因子：
2.7
通讯作者：
Hori, Tomoharu
中科院分区：
文献类型：
--
作者：
Nohara, Daisuke;Hori, Tomoharu
长期随机入流预测可以潜在地改善水库调度的决策。然而，它们仍然没有被广泛纳入实际的水库管理。原因之一可能是，随机流入预测中包含的各种类型的不确定性的影响尚未得到充分澄清，从而使水库管理人员认识到其使用的优点。因此，随机入流预测的不确定性对长期水库调度干旱管理的影响进行了研究，以分析最影响水库运行性能改善的不确定性。本文引入可靠性和区分度两个指标来表征随机预测的不确定性。采用随机动态规划（SDP）方法，结合水库调度优化过程，进行了水库供水调度的Monte Carlo模拟，并考虑了长期随机入流预测，通过改变两个不确定性指标来控制人工生成的任意不确定性。使用简化的水库盆地进行了案例研究，其数据来自日本的Sameura水库盆地，SDP具有更精细的离散化设置。结果表明，随机流入预测的不确定性对作者以前的工作的影响的额外含义。
Long-term stochastic inflow predictions can potentially improve decision making for reservoir operations. However, they are still not widely incorporated into actual reservoir management. One of the reasons may be that impacts of various types of uncertainty contained in stochastic inflow predictions have not been sufficiently clarified, thus enabling reservoir managers to recognize the advantages of their use. Impacts of uncertainties of stochastic inflow prediction on long-term reservoir operation for drought management are therefore investigated in order to analyze the kind of uncertainty that most affects improvements in the performance of reservoir operations. Two indices, namely reliability and discrimination, are introduced here to represent two major attributes of a stochastic prediction's uncertainty. Monte Carlo simulations of reservoir operations for water supply are conducted, coupling with optimization process of reservoir operations by stochastic dynamic programming (SDP) considering long-term stochastic inflow predictions, which are artificially generated with arbitrary uncertainties controlled by changing the two uncertainty indices. A case study was conducted using a simplified reservoir basin of which data were derived from the Sameura Reservoir basin in Japan with finer discretization settings for SDP. The results demonstrated the additional implication of the effect of stochastic inflow prediction's uncertainty on the authors' previous work.