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You are here : eLibrary : IAHR World Congress Proceedings : 34th Congress - Brisbane (2011) : THEME 4: Responding to Shifting Water Resources : Optimal operation of selective withdrawal system using fitted-q algorithm in a reservoir
Optimal operation of selective withdrawal system using fitted-q algorithm in a reservoir
Author : H. Yajima1,2, A.F. Castelletti 2,3, R. Soncini-Sessa3 and E. Weber 3
A reinforcement learning approach was developed and applied to design efficient management policies for selective withdrawal system with the purpose of meeting established water quality/quantity targets both in-reservoir and downstream. Structured design of experiment simulations was performed by a 1D hydrodynamic-ecological model of DYRESM-CAEDYM to generate a learning dataset over which a daily management policy was trained using fitted-Q algorithm based on extremely randomized trees. The approach was demonstrated on the management of Tono Dam reservoir. We set three objectives (algal bloom, sedimentation and water temperature) for the optimized operation. First we computed the operating policies corresponding to the extreme points of Pareto frontier obtained by only one objective, then the policies corresponding to regions of the Pareto frontier of potential interest for a compromised solution. The results indicated that this method could solve conflicting objectives for both water quality/quantity problems.
File Size : 2,438,458 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 34th Congress - Brisbane (2011)
Article : THEME 4: Responding to Shifting Water Resources
Date Published : 01/07/2011
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