基于果蝇优化算法的配电网故障定位

为解决配电网故障定位问题,提出了一种基于果蝇优化算法的故障定位方法。将原先果蝇优化算法中连续的位置坐标和搜索步长离散化,使其与馈线区段的状态信息相联系。对于单电源辐射状配电网和多电源复杂配电网建立了相应的目标函数,分别针对单一故障、含信息畸变的单一故障、多重故障、含信息畸变的多重故障等四种场景进行了测试,测试结果验证了所提出方法的准确性和有效性。与蝙蝠算法、粒子群算法、遗传算法相比,果蝇优化算法在多重故障定位问题中表现出了良好的寻优能力和更快的收敛速度。

Fault location of power distribution network based on fruit fly optimization algorithm

To solve the problem of fault location of power distribution network, a fault location method based on fruit fly optimization algorithm is put forward. The continuous location coordinates and search steps of the original fruit fly optimization algorithm are discretized to link with the status information of feeder sections. Objective functions are established for radial distribution network with single power supply and complex distribution network with multiple power supplies. Four fault scenarios including single fault, single fault with information distortion, multiple faults and multiple faults with information distortion are tested respectively, and the test results validate the accuracy and effectiveness of the proposed method. Compared with bat algorithm, particle swarm optimization and genetic algorithm, fruit fly optimization algorithm turns out to be good at finding an optimal solution to multiple faults location problems with a faster convergence speed. This work is supported by National Natural Science Foundation of China (No. 51467012).