Knowledge-based genetic algorithm for unit commitment

Aldridge, C.J. and McKee, S. and McDonald, J.R. and Galloway, S.J. and Dahal, K.P. and Bradley, M.E. and Macqueen, J.F. (2001) Knowledge-based genetic algorithm for unit commitment. IEE Proceedings Generation Transmission and Distribution, 148 (2). pp. 146-152. ISSN 1350-2360 (https://doi.org/10.1049/ip-gtd:20010022)

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Abstract

A 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.

ORCID iDs

Aldridge, C.J., McKee, S., McDonald, J.R. ORCID logoORCID: https://orcid.org/0000-0002-7078-845X, Galloway, S.J. ORCID logoORCID: https://orcid.org/0000-0003-1978-993X, Dahal, K.P., Bradley, M.E. and Macqueen, J.F.;
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