基于改进二进制灰狼优化算法的配网故障定位

灰狼算法具有结构简单、概念清晰、易实现和全局性能好等优点，但由于存在后期收敛速度慢、局部搜索能力弱等缺点。为提高配网故障定位的准确性和快速性，对灰狼优化算法进行了改进。首先，由于配网故障定位方法可以把问题表示为0~1整数规划问题，故引入转换函数，以解决算法在二进制空间里位置更新问题。然后引进动态权重策略，以平衡算法的全局搜索能力和局部搜索能力且加快算法收敛速度。最后加入概率扰动策略，使算法避免过早陷入局部收敛。本文通过配网故障的算例分析来验证改进二进制灰狼优化算法的可行性和高效性。

Fault location of distribution network based on improved binary gray

The gray wolf algorithm has the advantages of simple structure, clear concept, easy implementation, good global performance, etc., but it has the disadvantages of slow convergence and weak local search ability in the later period. In order to improve the accuracy and rapidity of the fault location of the distribution network, the grey wolf optimization algorithm is improved. First of all, because the network fault location method can represent the problem as 0~1 integer programming problem, the conversion function is introduced to solve the problem of location update in binary space. Then the dynamic weight strategy is introduced to balance the global search capability and local search capability of the algorithm and accelerate the convergence speed of the algorithm. Finally, a probabilistic perturbation strategy is added to avoid premature local convergence of the algorithm. In this paper, the feasibility and efficiency of the improved binary grey wolf optimization algorithm are verified by an example.