Particle swarm optimization (PSO) is a new swarm intelligence optimization technique originating from artificial life and evolutionary computation. The algorithm completes the optimization through following the personal best solution of each particle and the global best value of the whole swarm. PSO can be implemented with ease and few parameters need to be tuned. It has been successfully applied in many areas. Based on the inspection of a large number of domestic and foreign literature, the basic principles of PSO are presented, the main research results of applying PSO in following aspects relevant to electric power systems, such as power system expansion planning, maintenance scheduling, short-term generation scheduling, unit commitment , load frequency control, optimal power flow, reactive power optimization, harmonic analysis and capacitor configuration, parameter identification, state estimation and optimal design, are overall presented in detail in this paper. The research trends towards the application in the future is predicated.