An improved competitive swarm optimizer (ICSO) is proposed for large scale power system economic dispatch.The CSO is fundamentally inspired by the particle swarm optimization (PSO).It is with advantages of simple principle,easy implementation,and strong search ability.Based on the analysis of the disadvantages of the CSO,an improved loser updating strategy and an adaptive adjusting strategy of control parameter are proposed to balance the local and the global researching abilities.Four cases are employed to comparatively demonstrate the ICSO's viability and effectiveness from different perspectives of economy,convergence,and robustness.Simulation results indicate that the ICSO is with better performance and can be used as a reliable method for large-scale ED.%提出了一种求解大规模电力系统经济调度(Economic Dispatch,ED)问题的改进竞争群优化算法(Improved Competitive Swarm Optimizer,ICSO).CSO算法本质上受粒子群优化PSO算法所启发,具有原理简单,容易实现,搜索能力强等特点.在分析CSO算法存在的不足的基础上,提出了相应的劣质个体改进更新策略和控制参数自适应调节策略,以更好地平衡局部搜索和全局搜索.通过4个算例从经济性、收敛性、鲁棒性等多维角度对比分析了ICSO算法的可行性和有效性.算例仿真结果表明,ICSO具有较好的优化性能,可作为大规模ED问题的可靠求解方法.
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