Fast solution technique for unit commitment by particle swarm optimisation and genetic algorithm

In solving the Unit Commitment (UC) problem, two types of decision variables need to be determined: the start/shut down status and the output of power generation. Efficiently calculating the optimal commitment (on/off) and Economic Dispatch (ED) generations of the units at a sequence of times in the scheduling period is known as a challenge issue. In this paper, the proposed integrated PSO/GA approach of UC using Genetic Algorithm (GA) consists of repeating the process of ED employing modified Particle Swarm Optimisation (PSO) and minimising the total objective function for combinatorial units over all scheduled periods. The performance of the integrated PSO/GA approach is compared with results of other algorithms in the literature used to solve the UC problem. The comparison shows that the integrated PSO/GA approach is efficient in terms of computational time while providing good solutions.