An intelligent binary particle swarm optimization for unit commitment problem

This paper presents an intelligent binary particle swarm optimization (IBPSO) scheme with the Lambda-iteration method to solve the unit commitment problem (UCP). The UCP is considered as two linked optimization sub-problems: the unit-scheduled problem that can be solved by the BPSO method for the minimization of the transition cost, and the economic dispatch (ED) problem that can be solved by the Lambda-iteration method for the minimization of the production cost. Problem formulation of the UC takes into consideration the minimum up and down time constraints, start-up cost, and spinning reserve and is defined as the minimization of the total objective function while satisfying all the associated constraints. Problem formulation, representation, and the simulation results for a ten generator-scheduling problem are presented.