(untitled) (Nigerian Journal of Technology, 2022)
Generation Scheduling is a complex optimisation problem. The aim is to get an optimal combination of generating units for optimal operation. In this paper, Genetic Algorithm (GA) is presented as a viable optimisation tool to solve a fuel cost-based unit-commitment problem. The power system network adopted for the study is a 10-generator network. The prime objective here is to prepare the best economic start-up and shutdown schedules of the generators which meets the forecasted load demand plus reserve for a particular time interval while at the same time satisfying various system constraints. The implementation was done with the GA Toolbox in MATLAB 2018a. Results obtained were compared to the ones obtained with Lagrangian Relaxation optimisation technique and the comparison shows that Genetic Algorithm led to a slight reduction in fuel cost by ₦ 522,452.20 for the 24-hour period.