Reservoir Operation Using Bayesian Inferencing and Balancing Rules

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: Bayesian analysis | Reservoirs | Computer programming | Decision support systems | Optimization models | Water resources | Probability | Water flow | Oregon | United States | North America

Services: Buy this book/Buy this article

 

Return to search