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• W2147322969 abstract "Most models for reservoir operation optimization have employed either deterministic optimization or stochastic dynamic programming algorithms. This paper develops sampling stochastic dynamic programming (SSDP), a technique that captures the complex temporal and spatial structure of the streamflow process by using a large number of sample streamflow sequences. The best inflow forecast can be included as a hydrologic state variable to improve the reservoir operating policy. A case study using the hydroelectric system on the North Fork of the Feather River in California illustrates the SSDP approach and its performance." @default.
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• W2147322969 date "1990-03-01" @default.
• W2147322969 modified "2023-10-09" @default.
• W2147322969 title "Sampling stochastic dynamic programming applied to reservoir operation" @default.
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• W2147322969 doi "https://doi.org/10.1029/wr026i003p00447" @default.
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