基于改进布谷鸟算法的有源配电网故障定位方法

Fault Location Method of Active Distribution Network Based on Improved Cuckoo Algorithm

  • 摘要: 现有智能优化算法在求解含分布式电源(Distributed generation,DG)配电网故障定位问题时,存在迭代次数多、收敛速度慢、易陷入局部最优解和容错性较差等问题,为此,提出了一种具有新移动策略的布谷鸟算法(New movement strategy cuckoo search algorithm,NMS-CS)。算法在考虑大容量DG接入配电网的情况下,引入了带有方向性的馈线终端(Feeder terminal unit,FTU)状态编码,建立了适应DG投切的开关函数和目标函数;在传统布谷鸟算法的基础上通过改进步长、提出新的方向参数提高了算法前期全局寻优的能力和后期搜索的精度,提出潜在搜索空间参数来确定计算方向,进而提高了算法收敛速度,实现有源配电网快速故障定位。仿真试验结果表明,NMS-CS算法在单点、多点以及信息畸变故障定位中均能实现准确定位,同其他优化算法相比具有更少的迭代次数和更短的收敛时间,有效缩短故障处理时间。

     

    Abstract: The existing intelligent optimization algorithms have many problems in solving the fault location problem of distribution network with distributed generation(DG), such as many iterations, slow convergence speed, easy to fall into the local optimal solution, poor fault tolerance, etc. A cuckoo search algorithm with a new movement strategy(NMS-CS) is proposed. The feeder terminal unit(FTU) state coding with directional is introduced when considering the large capacity DG access to the distribution network, and the switch function and objective function adapted to the DG switching are established. Based on the traditional cuckoo algorithm, the algorithm improves the ability of global optimization in the early stage and the accuracy of the late search by improving the length and proposing new direction parameters. The potential search space parameters are proposed to determine the calculation direction, and then improve the convergence speed of the algorithm, and realize the rapid fault location of active distribution network. Simulation results show that the NMS-CS algorithm can achieve accurate location in single-point, multi-point and information distortion fault location, and has fewer iterations and shorter convergence time compared with other optimization algorithms. Effectively shorting the troubleshooting time.

     

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