基于改进秃鹰搜索算法的含分布式电源配电网分区故障定位

为解决含分布式电源多分支配电网故障定位中存在快速性和准确性难以兼顾的问题，提出了一种基于改进秃鹰搜索算法的分区故障定位模型。首先利用Sinusoidal映射的均匀分布特性生成初始化种群，通过交叉算子、非均匀变异算子和翻筋斗觅食策略来改进秃鹰的位置更新方式，提高算法的开采和勘探能力。其次构建考虑分布式电源的开关函数和目标函数，在此基础上借鉴“黑盒方法”建立含分布式电源配电网等效分区模型，并加入定位矫正机制保障定位的准确率。最后在含分布式电源多分支配电网中进行仿真验证。与传统的秃鹰搜索算法分区定位模型相比，求解速度平均提高了30.5%，准确率平均提高了1.72%。且在不同故障位置和不同畸变点数情况下，改进秃鹰搜索算法分区定位模型均能够快速准确地定位出故障所在区段。

Fault location of a distribution network hierarchical model with a distribution generator based on IBES

There is a problem that it is difficult to balance the speed and accuracy of fault location in a multi-branch distribution network with a distributed generator. Thus a fault location model based on an improved bald eagle search algorithm is proposed. First, this paper uses the uniform distribution characteristics of sinusoidal mapping to generate the initial population. It also improves the position update method of the bald eagle through a crossover operator, the non-uniform mutation operator and the somersault foraging strategy, and enhances the mining and exploration capabilities of the algorithm. Secondly, the switching function and objective function considering the distributed generator are constructed. An equivalent hierarchical model of a distribution network with a distributed generator is established by referring to the "black box method", and a location correction mechanism is added to ensure the accuracy of location. Finally, a simulation is carried out in the multi-branch distribution network with a distributed generator. Compared with the traditional bald eagle search algorithm zoning location model, solution speed is improved by 30.5% and accuracy is improved by 1.72% on average. In addition, under different fault locations and different distortion points, the improved bald eagle search algorithm zone location model can quickly and accurately locate the fault zone. This work is supported by the National Natural Science Foundation of China (No. 71263043 and No. 61763040).