改进布谷鸟搜索算法在电力系统优化潮流中的应用

发布时间：2018-05-02 10:31

本文选题：布谷鸟算法 + 动态参数　；参考：《电力系统及其自动化学报》2017年10期

【摘要】：针对优化潮流的特点以及布谷鸟搜索算法收敛速度慢和缺乏活力等问题,从动态参数和步长方程两个方面进行改进,提出了改进的布谷鸟搜索算法来解决优化潮流问题。该算法把原来是常数的两个参数改进为动态变化的参数,随着迭代次数的增加,发现概率和步长因子两个参数按一定的规律递减,使算法在初期能增加种群的多样性,后期能更好地微调以找到最优解;同时,提出了一个具有最优解导向的搜索步长方程以提高算法的局部搜索能力和收敛速度。用改进的布谷鸟算法计算IEEE30系统的优化潮流,仿真结果表明该算法能够有效地提高收敛速度和计算精度。
[Abstract]:In view of the characteristics of optimal power flow and the slow convergence speed and lack of vitality of the Cuckoo search algorithm, this paper proposes an improved Cuckoo search algorithm to solve the optimal power flow problem from the two aspects of dynamic parameters and step size equations. With the increase of iteration times, it is found that the two parameters of probability and step size decrease according to certain law, so that the algorithm can increase the diversity of population in the initial stage. At the same time, a search step equation with optimal solution orientation is proposed to improve the local search ability and convergence speed of the algorithm. The improved Cuckoo algorithm is used to calculate the optimal power flow of the IEEE30 system. The simulation results show that the algorithm can effectively improve the convergence speed and computational accuracy.
【作者单位】：重庆邮电大学自动化学院复杂系统分析与控制研究中心;武汉铁路职业技术学院机车车辆工程系;
【基金】：国家自然科学基金资助项目(51207064,51507024) 重庆市科委科技资助项目(KJI500401)
【分类号】：TM744

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