Unit commitment is a complex decision-making process because of multiple constraints which must not be violated while nding the optimal or a near-optimal commitment schedule. This paper discusses the application of genetic algorithms for determining short term commitment order of thermal units in power generation. The objective of the optimal commitment is to determine the on/o states of the units in the system to meet the load demand and spinning reserve requirement at each time period such that the overall cost of generation is minimum, while satisfying various operational constraints. The paper examines the feasibility of using genetic algorithms, and reports preliminary results in determining a near-optimal commitment order of thermal units in a studied power system. A version of this report will appear in the Proceedings of 5th IEEE International Conference on Tools with Arti cial Intelligence, November 8-11, 1993, Boston, USA. 1
Dipankar Dasgupta, Douglas R. McGregor