摘要
针对电力系统最优潮流计算的问题提出一种基于梯度蜂群混合算法GABC。利用梯度算法的快速寻优特性得到某一局部极值,然后采用蜂群算法的全局寻优能力跳出该局部极值,并经过反复交替迭代最终找到问题的最优解。通过对IEEE5节点系统的计算结果表明改进后的人工蜂群算法可较好的处理最优潮流约束条件,有效提高基本蜂群算法的全局寻优能力和收敛精度。在处理最优潮流问题上具有一定的有效性和优越性。
Aiming at optimal power flow calculation problem in power system,this paper presents a new method of hybrid artificial bee colony algorithm based on gradient method GABC.Firstly,the new algorithm used quickness searching of gradient method to obtain a local minimum,then by utilizing the abilities of global searching of artificial bee colony algorithm,it escaped from trapping this local minimum.At last,the global minimum was achieved through iterative computation.Simulation experiments of IEEE5 system show that the improved algorithm can be better dealt with optimal flow constraints in dealing with the issue of optimal power flow.This method can also find preferable results and its correctness and validity is proven by a series of tests and computation,and that the algorithms can be widely applied to the areas of power system planning and operation.
出处
《计算技术与自动化》
2011年第4期98-102,共5页
Computing Technology and Automation
基金
广西研究生创新计划项目(2011105940811M01)
关键词
最优潮流
人工蜂群算法
梯度
optimal power flower
artificial bee colony algorithm
gradient method
