Title :
Unit commitment using particle swarm optimization combined with Lagrange relaxation
Author :
Sriyanyong, P. ; Song, Y.H.
Author_Institution :
Brunel Inst. of Power Syst., Brunel Univ., Uxbridge, UK
Abstract :
This paper proposes particle swarm optimization (PSO) combined with Lagrange relaxation method (LR) for solving unit commitment (UC). The proposed approach employs PSO algorithm for optimal settings of Lagrange multipliers. The feasibility of the proposed method is demonstrated for 4 and 10-unit systems, respectively. The test results are compared with those obtained by LR, genetic algorithm (GA) and hybrid particle swarm optimization (HPSO) in terms of solution quality. Simulation results show that the proposed method can provide a better solution.
Keywords :
particle swarm optimisation; power generation scheduling; Lagrange multipliers; Lagrange relaxation method; genetic algorithm; particle swarm optimization; unit commitment; Costs; Dynamic programming; Lagrangian functions; Linear programming; Particle swarm optimization; Power generation; Power system dynamics; Production; Spinning; System testing;
Conference_Titel :
Power Engineering Society General Meeting, 2005. IEEE
Print_ISBN :
0-7803-9157-8
DOI :
10.1109/PES.2005.1489390