基于改进蚁群算法的配电网优化规划

提出了一种基于改进蚁群算法的配电网优化规划算法．对于给定的配电网模型，该算法根据各配电网站点建立初始信息素矩阵，然后利用蚁群算法所特有的路径寻优功能来搜索配电网布局路径，并结合改进信息素刷新的方式和在蚁群搜索过程中引入曼哈顿距离以及弹性伸缩调节因子，使蚁群以较快的速度找到当前布局上的最优路径．通过具体的算例表明，该算法比一般蚁群优化规划算法具有更高的计算效率和优秀的全局搜索能力，同时有效地克服了在求解配电网规划问题时蚁群在局部最优解上的巡回而存在的效率不高以及未成熟收敛等现象．

Power Distribution Network Optimization Planning Based on Improved Ant Colony Algorithm

A new method of power network planning based on improved ant colony algorithm is presented. For a given power network model, once establishing initialization pheromone matrix, searching the path depending on the special ability of ant colony, combining with an improved method of refreshing pheromone, Manhattan distance and the thought of flexibility, the best power distribution network planning path is found at a higher rate only if it exits. Some examples confirm the computing efficiency and global convergence to solve the difficulty of the premature convergence due to repeat calculation in the existing ant colony algorithm.