An Application of Particle Swarm Optimization (PSO) to Dynamic Unit Commitment Problem for the Western Area of Saudi Arabia

Unit commitment (UC) in power systems typically involves properly scheduling the on/off states as well as the real power outputs (economic dispatch) of all resources (generators/units) in the system. In addition to fulfill a large number of system constraints, the UC meets forecasted load demand calculated in advance, plus the spinning reserve requirement at each time interval, such that the total cost (mainly fuel cost) is minimum. In this paper particle swarm optimization (PSO) is applied to minimize cost, emission or costemission of the Unit Commitment problem. For unit commitment both cost and emission are considered. Actually cost and emission are trade-off. If cost increases, emission decreases and vice-versa. Real power is forecasted and used in the Unit Commitment of the Western Area of Saudi Arabia. The total cost for generation for 24 h is 4332905$ and the emission is 193479 ton.