Implications of the Value of Hydrologic Information to Reservoir Operations -- Learning From the Past

Finally we couple the data mining procedure with conventional reservoir optimization techniques to build an enhanced stochastic dynamic programming (SDP) model. The enhanced SDP model is applied to the Shelbyville Reservoir, IL, and then compared to two classic SDP formulations. From a data mining procedure, past month's inflow, current month's inflow, past month's release, and past month's Palmer drought severity index are found to be important state variables in the enhanced SDP model formulations for Shelbyville Reservoir. The study indicates that the enhanced SDP model resembles historical records more closely yet provides lower expected average annual costs than either of the two classic formulations (25.4% and 4.5% reductions).

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Civil Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Hejazi, Mohamad Issa

Contributors dc:contributor

• Cai, Ximing

• Hydrology

Language dc:language

eng

Identifier

(MiAaPQ)AAI3392065

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/83403