摘要
针对基本细菌群体趋药性(Bacterial Colony Chemotaxis,BCC)算法中存在的缺陷进行改进,在基本BCC算法中引入了带有权重系数的细菌变速公式,使算法能较快收敛在几个最优解周围并进行细致搜索,从而寻找到全局的最优解;引入了细菌感知范围的动态调整机制,提高了算法的寻优精度;引入了记录本,把细菌寻优过程中的最优值暂记在记录本里,从而避免了最优值被随机抛弃的情况。文章建立了基于最优潮流的可用输电能力的计算模型,并运用改进的细菌群体趋药性算法来求解该模型。通过以IEEE-30节点测试系统为例进行仿真计算,并与基本BCC算法的计算结果进行了比较,结果表明IBCC算法能以更快的速度得到最优解,其性能明显优于基本BCC算法。
In view of the defects existing in the basic Bacterial Colony Chemotaxis ( BCC) algorithm, in this paper, the bacteria variable speed formula with weight coefficients was introduced into the basic BCC algorithm, by which the algorithm could fast converge around several optimal solutions and search thoroughly so as to find the global optimal so-lution.The dynamic adjustment mechanism of the bacteria perception scope was also introduced, which improved the optimization precision of the algorithm.The notebook was adopted in the study, on which the optimal value in the op-timization-searching process of the bacteria could be recorded temporarily so as to avoid the optimum being abandoned by random.In this paper, the calculation model of the available transmission capacity (ATC) was constructed based on the optimal power flow ( OPF) , and the model was solved with the improved BCC algorithm.With the IEEE-30 node testing system as an example, simulation calculation was made and the calculated results were compared with those obtained from the basic BCC algorithm.The results showed that the IBCC algorithm could get the optimal solu-tion with a faster speed, and its performance was superior to that of the basic BCC algorithm.
出处
《电测与仪表》
北大核心
2015年第10期23-28,共6页
Electrical Measurement & Instrumentation
关键词
细菌群体趋药性算法
可用输电能力
变速公式
动态调整
最优潮流
bacterial colony chemotaxis algorithm
available transmission capacity (ATC)
variable speed formula
dynamic adjustment
optimal power flow (OPF)