Title :
Unit Commitment Using Particle Swarm-Based-Simulated Annealing Optimization Approach
Author :
Sadati, Nasser ; Hajian, Mahdi ; Zamani, Majid
Author_Institution :
Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran
Abstract :
In this paper, a new approach based on hybrid particle swarm-based-simulated annealing optimization (PSO-B-SA) for solving thermal unit commitment (UC) problems is proposed. The PSO-B-SA presented in this paper solves the two sub-problems simultaneously and independently; unit-scheduled problem that determines on/off status of units and the economic dispatch problem for production amount of generating units. Problem formulation of UC is defined as minimization of total objective function while satisfying all the associated constraints such as minimum up and down time, production limits and the required demand and spinning reserve. Simulation results show that the proposed approach can outperform the other solutions.
Keywords :
particle swarm optimisation; power generation dispatch; power generation economics; power generation scheduling; simulated annealing; thermal power stations; economic dispatch problem; particle swarm optimization; simulated annealing optimization; thermal unit commitment; unit-scheduled problem; Annealing; Costs; Dynamic programming; Hybrid intelligent systems; Linear programming; Particle swarm optimization; Power generation economics; Processor scheduling; Production; Spinning;
Conference_Titel :
Swarm Intelligence Symposium, 2007. SIS 2007. IEEE
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0708-7
DOI :
10.1109/SIS.2007.367951