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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


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:
Provided by: Bradford Scholars
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