Browse

Value of seasonal flow forecasts in Bayesian stochastic programming

Cited 0 time in Web of Science Cited 0 time in Scopus
Authors
Kim, Young-Oh; Palmer, Richard N.
Issue Date
1997
Publisher
American Society of Civil Engineers
Citation
Journal of Water Resources Planning and Management, 123(6), 327-335
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.
ISSN
0733-9496
Language
English
URI
https://hdl.handle.net/10371/67629
Files in This Item:
There are no files associated with this item.
Appears in Collections:
College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Civil & Environmental Engineering (건설환경공학부)Journal Papers (저널논문_건설환경공학부)
  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse