基于BAS-IGA的含分布式电源配电网故障定位

针对遗传算法解决含分布式电源配电网故障区段定位易早熟收敛的问题,提出了一种基于天牛须搜索算法和改进遗传算法相结合的故障定位方法。该方法首先利用天牛须搜索算法产生高质量的初始种群,其次通过构造遗传算法数学模型、优化3种遗传算子和调节交叉变异概率对遗传算法进行改进,最终经遗传迭代产生最优解,达到精确定位故障区段的目的。以IEEE33节点配电网模型为例,分别针对单重故障、多重故障以及信息畸变情况进行仿真。仿真结果表明,提出的优化算法定位准确率为100%,且收敛速度快、容错性好。

Fault Location of Distribution Network with Distribution Generations Based on BAS-IGA

Considering that premature convergence will occur when genetic algorithm(GA)is used to solve the problem of fault location of distribution network with distributed generations(DGs),a fault location method based on the combination of beetle antennae search(BAS)algorithm and improved genetic algorithm(IGA)is proposed in this paper.First,this method uses the BAS algorithm to generate a high-quality initial population.Then,GA is improved by constructing a GA mathematical model,optimizing three genetic operators,and adjusting the probability of cross mutation.Finally,the optimal solution is generated through genetic iterations to achieve the purpose of accurate fault location.An IEEE 33-node distribution network model is taken as an example,and simulations are performed for the cases of single fault,multiple faults,and information distortion,respectively.Simulation results show that the proposed optimization algorithm has a location accuracy of 100%,as well as a fast convergence speed and satisfying fault tolerance.