Journal ArticleDOI
Value of seasonal flow forecasts in Bayesian stochastic programming
Young-Oh Kim,Richard N. Palmer +1 more
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TLDR
In this paper, a Bayesian Stochastic Dynamic Programming (BSDP) model was proposed to investigate the value of seasonal flow forecasts in hydropower generation, and the proposed BSDP framework generated monthly operating policies for the Skagit Hydropower System (SHS) which supplies energy to the Seattle metropolitan area.Abstract:
This paper presents a Bayesian Stochastic Dynamic Programming (BSDP) model to investigate the value of seasonal flow forecasts in hydropower generation. The proposed BSDP framework generates monthly operating policies for the Skagit Hydropower System (SHS), which supplies energy to the Seattle metropolitan area. The objective function maximizes the total benefits resulting from energy produced by the SHS and its interchange with the Bonneville Power Administration. The BSDP-derived operating policies for the SHS are simulated using historical monthly inflows, as well as seasonal flow forecasts during 60 years from January 1929 through December 1988. Performance of the BSDP model is compared with alternative stochastic dynamic programming models. To illustrate the potential advantage of using the seasonal flow forecasts and other hydrologic information, the sensitivity of SHS operation is evaluated by varying (1) the reservoir capacity; (2) the energy demand; and (3) the energy price. The simulation results demonstrate that including the seasonal forecasts is beneficial to SHS operation.read more
Citations
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Journal ArticleDOI
Simulation-optimization modeling: a survey and potential application in reservoir systems operation.
TL;DR: Simulation, optimization and combined simulation–optimization modeling approach are discussed and an overview of their applications reported in literature is provided to help system managers decide appropriate methodology for application to their systems.
Journal ArticleDOI
Reservoir optimization using sampling SDP with ensemble streamflow prediction (ESP) forecasts
B.A. Faber,Jery R. Stedinger +1 more
TL;DR: Frequently-updated ESP forecasts in a real-time SSDP reservoir system optimization model (and a simpler two-stage decision model) provide more efficient operating decisions than a sophisticated SSDP model employing historical time series coupled with snowmelt-season volume forecasts.
Journal ArticleDOI
An overview of the optimization modelling applications
TL;DR: The comprehensive reviews on the use of various programming techniques for the solution of different optimization problems have been provided and conclusions are drawn where gaps exist and more research needs to be focused.
Journal ArticleDOI
Derived Operating Rules for Reservoirs in Series or in Parallel
Jay R. Lund,Joel Guzman +1 more
TL;DR: In this article, a variety of derived single-purpose operating policies for reservoirs in series and in parallel for water supply, flood control, hydropower, water quality, and recreation are presented.
Journal ArticleDOI
Evaluation of the parameterization-simulation-optimization approach for the control of reservoir systems
TL;DR: The investigation shows that PSO yields solutions that are not inferior to those of the benchmark methods and, simultaneously, it has several theoretical, computational, and practical advantages.
References
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Book
Dynamic Programming
TL;DR: The more the authors study the information processing aspects of the mind, the more perplexed and impressed they become, and it will be a very long time before they understand these processes sufficiently to reproduce them.
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Probability Concepts in Engineering Planning and Design
TL;DR: This research attacked the mode confusion problem by developing a modeling framework called “model schizophrenia” to estimate the posterior probability of various modeled errors.
Journal ArticleDOI
Reservoir Management and Operations Models: A State‐of‐the‐Art Review
TL;DR: The objective of this paper is to review the state-of-the-art of mathematical models developed for reservoir operations, including simulation, which include linear programming, dynamic programming, nonliner programming, and simulation.
Journal ArticleDOI
Stochastic dynamic programming models for reservoir operation optimization
TL;DR: The authors developed a stochastic dynamic programming model which employs the best forecast of the current period's inflow to define a reservoir release policy and to calculate the expected benefits from future operations.
Journal ArticleDOI
Sampling stochastic dynamic programming applied to reservoir operation
TL;DR: In this article, sampling stochastic dynamic programming (SSDP) is used to capture the complex temporal and spatial structure of the streamflow process by using a large number of sample streamflow sequences.