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A knowledge-based genetic algorithm for unit commitment

By C.J. Aldridge, S. McKee, J.R. McDonald, S.J. Galloway, Keshav P. Dahal, M.E. Bradley and J.F. Macqueen

Abstract

NoA genetic algorithm (GA) augmented with knowledge-based methods has been developed for solving the unit commitment economic dispatch problem. The GA evolves a population of binary strings which represent commitment schedules. The initial population of schedules is chosen using a method based on elicited scheduling knowledge. A fast rule-based dispatch method is then used to evaluate candidate solutions. The knowledge-based genetic algorithm is applied to a test system of ten thermal units over 24-hour time intervals, including minimum on/off times and ramp rates, and achieves lower cost solutions than Lagrangian relaxation in comparable computational time

Topics: Genetic algorithm, Knowledge-based methods, Economic dispatch problem, Knowledge-based genetic algorithm
Year: 2001
DOI identifier: 10.1049/ip-gtd:20010022
OAI identifier: oai:bradscholars.brad.ac.uk:10454/3689
Provided by: Bradford Scholars
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