基于反向学习的人工蜂群算法的电力系统最优潮流  

Power System Power Flow Optimization Based on Opposition-based Artificial Bee Colony Algorithm

作　　者：刘前进[1] 许慧铭 施超[1] 

机构地区：[1]华南理工大学电力学院,广东广州510640

出　　处：《华北电力技术》2014年第8期1-5,共5页North China Electric Power

摘　　要：以发电机大气污染物排放量最小为目标函数,建立一种电力系统最优潮流模型,并提出一种基于反向学习的人工蜂群算法进行求解。IEEE-30节点系统仿真分析结果表明,与其它算法进行相比,提出的算法能够有效降低发电机大气污染物排放量,算法简单,具有更好的寻优能力和收敛特性。A reactive power optimization model is established to realize the lowest atmospheric pollutants emission of generation units and an opposition-based artificial bee colony algorithm is proposed to solve this optimization prob- lem. The simulation results of IEEE 30-bus system show that the proposed algorithm has a simple framework and quick convergence characteristic and the pollutants emission of generation units can be effectively reduced by this al- gorithm than other algorithms.

关 键 词：最优潮流 无功优化 人工蜂群算法 反向学习 节能减排 

分 类 号：TM72[电气工程—电力系统及自动化]