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Improved Dynamic Programming for Reservoir Operation Optimization with a Concave Objective Function
DOI:10.1061/(ASCE)WR.1943-5452.0000205.png)
Abstract
En 中文
Diminishing marginal utility is an important characteristic of water resources systems. With the assumption of diminishing marginal utility (i.e., concavity) of reservoir utility functions, this paper derives a monotonic relationship between reservoir storage and optimal release decision under both deterministic and stochastic conditions, and proposes an algorithm to improve the computational efficiency of both deterministic dynamic programming (DP) and stochastic dynamic programming (SDP) for reservoir operation with concave objective functions. The results from a real-world case study show that the improved DP and SDP exhibit higher computational efficiency than conventional DP and SDP. The computation complexity of the improved DP and SDP is O(n) (order of n, the number of state discretization) compared to O(n(2)) with conventional DP and SDP. DOI: 10.1061/(ASCE)WR.1943-5452.0000205. (C) 2012 American Society of Civil Engineers.
Keywords:
Concavity
Monotonicity
Dynamic programming
Reservoir operation
Journal
IF:
4.7
Papers:
8.1K
Citations:
1.6W
Organization
Cited Papers
Reservoir optimization using sampling SDP with ensemble streamflow prediction (ESP) forecasts
JOURNAL OF HYDROLOGY
IF6.3

