广义蚁群与粒子群结合算法在电力系统经济负荷分配中的应用  

APPLICATION OF GENERALIZED ANT COLONY OPTIMIZAITON ALGORITHM INTEGRATED WITH PARTICLE SWARM OPTIMIZATION ALGORITHM IN ECONOMIC DISPATCH OF POWER SYSTEM

作　　者：侯云鹤[1] 鲁丽娟[1] 熊信艮[1] 吴耀武[1] 

机构地区：[1]华中科技大学电力工程系,湖北省武汉市430074

出　　处：《电网技术》2004年第21期34-38,共5页Power System Technology

摘　　要：提出了一种结合广义蚁群算法和粒子群算法的优化算法,并将其用于求解复杂的非凸、非线性的电力系统经济负荷分配问题。该结合算法同时具有广义蚁群算法的大规模寻优特性和粒子群算法的较强局部搜索能力,在确保全局收敛性的基础上,能够快速搜索到高质量的优化解。多个算例的仿真结果表明了该结合算法的有效性和可行性。An optimized algorithm in which the general ant colony optimization (GACO) is integrated with particle swarm optimization (PSO) is proposed and is applied to economic dispatch of a complicated, non-concex and nonlinear power system. This integrated algorithm possesses large scale search capability of generalized ant colony algorithm and better local search capability of particle swarm algorithm at the same time. Under the condition of ensuring global convergence, high quality optimization solution can be searched by the proposed algorithm. The simulation results of several calculation examples show that the proposed algorithm is effective and feasible.

关 键 词：粒子群算法 快速搜索 粒子群 局部搜索能力 仿真结果 广义蚁群算法 大规模 电力系统 负荷分配 寻优 

分 类 号：TM731[电气工程—电力系统及自动化] TP301.6[自动化与计算机技术—计算机系统结构]