基于人工蜂群算法的多目标最优潮流问题的研究  

Research on power flow optimization based on multi-objective 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：《电力系统保护与控制》2015年第8期1-7,共7页Power System Protection and Control

摘　　要：以污染气体排放量、网损最小为目标,建立多目标电力系统最优潮流数学模型,并提出一种基于人工蜂群的多目标算法对其进行求解。该算法利用外部存档技术来保存进化过程中已经找到的Pareto最优解,并在每次迭代后更新。最后根据模糊集理论从Pareto最优解集中选取最优折衷解,为决策者提供科学的决策依据。通过IEEE-30节点系统及IEEE-57节点系统的仿真,验证了该算法在求解大规模电力系统多目标问题上的有效性,相比其他多目标算法能有效避免局部收敛。Taking the minimum pollutant emission and active loss as objective functions,this paper builds a multi-objective optimization model for power flow optimization of power system.In the proposed algorithm,an external archive of non-dominated solutions is kept which is updated at each iteration.Moreover,a method based on fuzzy set theory is employed to extract one of the Pareto-optimal solutions set as the best compromise one to provide the scientific decision basis for decision-makers.Simulation of IEEE-30 bus system and IEEE-57 bus system testify that this algorithm can avoid the local convergence effectively compared with other multi-objective optimization algorithm.

关 键 词：最优潮流 无功优化 人工蜂群算法 多目标 污染气体排放 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TM715[自动化与计算机技术—控制科学与工程]