An Improved Particle Swarm Optimization Algorithm for Unit Commitment
This paper presents a new approach via multi particle swarm optimization (MPSO) to solve the unit commitment (UC) problem. A new strategy which can generate feasible particles and make the search space narrow within the feasible solutions is presented. Some particle swarms are generated by the new strategy, and location optimum solutions are searched in each particle swarm, then a new particle swarm is made up of location optimum solutions, and the global optimum solution is searching in this new particle swarm. The application of the new generating strategy in PSO can efficiently improve the global searching capability and escape from local minima. The simulation results show that the method is more efficient than genetic algorithm, and could obtain the global optimum solution more probably.
Wei Xiong Mao-jun Li Yuan-lin Cheng
School of Electrical & Information Engineering, Changsha University of Science and Technology, Chang Hunan Electric Power Design Institute, changsha 410007 China
国际会议
长沙
英文
21-25
2008-10-20（万方平台首次上网日期，不代表论文的发表时间）