Reservoir Operation Using Bayesian Inferencing and Balancing Rules

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by Emmanuel U. Nzewi, (A.M.ASCE), North Carolina A&T State Univ, Greensboro, United States,

Document Type: Proceeding Paper

Part of: Water Policy and Management: Solving the Problems

Abstract: The water resources problem addressed in this paper is real-time, multi-purpose reservoir operation. Specifically, daily, or at the most, weekly operations are considered. A hybrid modeling scheme is proposed. It entails the use a probabilistic dynamic programming scheme (which could include updating) and a Bayesian inferencing component. The model could be used as a simulation tool as well as a decision support module. Although intelligent reasoning models have been proposed in the literature, this one differs by the fact that the optimization component is closely coupled to the reasoning sub-model. Hydropower production as well as flow augmentation, flood flow attenuation and water supply are considered in the model development.

Subject Headings: Water resources | Reservoirs | Computer programming | Bayesian analysis | Decision support systems | Optimization models | Probability | Water flow |

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