Masters Theses
Date of Award
12-1999
Degree Type
Thesis
Degree Name
Master of Science
Major
Engineering Science
Major Professor
Robert E. Uhrig
Committee Members
Michael Vose, J. A. M. Boulet
Abstract
This thesis discusses the construction and use of a real-valued Genetic Algorithm To optimize weekly scheduling for TVA's Raccoon Mountain Pumped Storage facility.Pumped storage systems are primarily employed to meet peak load conditions and to replace power plants during scheduled maintenance outages. Scheduling for this facility involves determining when to pump water into an elevated reservoir and when to release the water for generation. Using a historical weekly load, a Genetic Algorithm was constructed and used to search for schedules that maximize monetary return. The Algorithm proves to be capable of finding schedules that optimize usage and simultaneously reduce peak system loads.
Recommended Citation
Thomas, Ryan, "A real-valued genetic algorithm for optimizing pumped storage scheduling. " Master's Thesis, University of Tennessee, 1999.
https://trace.tennessee.edu/utk_gradthes/10037