遗传-蚁群算法的配电网状态估计

Estimation of power distribution network state based on genetic algorithm and ant colony algorithm

针对单一遗传算法或者蚁群算法无法获得理想配电网状态估计结果,根据组合优势互补原理,提出基于遗传-蚁群算法的配电网状态估计方法。首先对当前配电网状态估计现状进行分析,并构建配电网状态数学模型,然后利用全局寻优性能强的遗传算法对配电网状态数学模型进行求解,最后采用局部寻优能力强的蚁群算法对遗传算法的解进行精细搜索,得到配电网状态的最优估计值。实验结果表明,该算法综合利用了遗传算法和蚁群算法的优点,有效避免了两种算法各自存在的不足,获得了更优的配电网状态估计结果。

Since the single genetic algorithm or ant colony algorithm can＇t obtain the desired estimation results of power dis- tribution network state, an estimation method of power distribution network state based on genetic algorithm and ant colony algo- rithm is proposed according to the principle of complementary advantages. The current estimation situation of the power distribu- tion network state is analyzed. The mathematical model of power grid state is constructed, and solved by means of the genetic al- gorithm with good global optimization ability. And then the ant colony algorithm with good local optimization ability is used to search the solution of genetic algorithm finely, so as to obtain the optimal estimation value of the power distributed state. The ex- perimental results show that the proposed algorithm uses the advantages of genetic algorithm and ant colony algorithm fully, avoids the shortcomings of the two algorithm effectively, and obtains better state estimation result of power distribution network.