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.
出处
《电网技术》
EI
CSCD
北大核心
2004年第21期34-38,共5页
Power System Technology
