低压电力线通信的双种群遗传蚁群路由算法

Dual population genetic optimization ant colony algorithm for low voltage power line communication

针对低压配电网动态变化的拓扑结构,给出一种双种群遗传蚁群算法。利用双种群的快速适应性和独立并行搜索能力,在动态范围内寻找最优解,采用定期交换彼此种群的优良解的方法,扩大全局解搜索空间,降低算法容易陷入局部最优的可能性,最终找出全局最优。仿真结果表明,所给算法能快速适应动态变化的低压电力线网络,提高全局收敛性与鲁棒性。

According to the topological structure of the dynamic change of the low voltage distribution network,a dual population genetic ant colony algorithm is presented.By using the dual population fast adaptability and independent ability of parallel search,the optimal solution can be found in the dynamic range,and after some regular exchange of the excellent solutions of each population,the global solution search space can be enlarged.Thus,the possibility that the algorithm is easy to fall into local optimum can be reduced,and the global optimum solution can be eventually found.Simulation results show that,the given algorithm can quickly adapt to the dynamic changes of low voltage power line network,and improve the global convergence and robustness.