Research On Fault Segment Location Method Of Distribution Network With Distributed Power Supply Based On Improved Quantum Genetic Algorithms

It is an important measure to improve the reliability and safety of power supply to locate and isolate the faults in as short a time as possible after the faults occur in the distribution network.In recent years,with the support of the natio nal policy,a large number of clean energy is connected to the distribution network in the form of distributed energy:,which Chchanges the power flow of distribution network from one-way power flow to two-way power flow,and recducces the accuracy of the original fault location method in the distribution network.Therefore,it is necessary to study a fault section lo cation method with high fault tolerance and suitable fo r distribution network with distributed generation.his paper draws lessons from the existing fault location methods at home and abroad.Based on the strong fault tolerance of the improved quantum genetic algorithm,a fault location method for distribution network with distributed generation based on the improved quantum genetie algorithm is proposed.Firstly.the characteristics of distributed generation and the influence of distributed generation on the original fault location method are studied.The traditional fault location method of distribution network based on quantum genetic algorithm is deep ly studied.Based on this,a fault location method stuitable for distributed power supply is studied,including redetfining the encoding mode of each suwitch,constructing the contact functioin between each switch and feeder aeeording to the encoding mode,and analyzing the fault tolerance ih the case offalse alarm and missed switch status information.The simulation results by MATLAB 2014 show that the propo sed fault seetion loation method can accurately locate the fault section of distribution network with distributed generation,and ha s strong fault tolerance.Secondly,the shortcomings of quantum genetic algorithm are analyzed and improved.The dynamic rotation angle strategy based on gradient descent method is used to update the quantum gate to improve the convergence speed of the algorithm.Discreteness analysis is introduced to determine whether the algorithm is trapped in the local optimum.Tent chaotic optimization method is used to jump out of the local optimum and improve the global optimization ability of the algorithm.The improved algorithm is verified by classical test function.Finally,the improved algorithm is applied to the IEEE69 node distribution network with distributed generation for simulation analysis.The results show that the improved quantum genetic algorithm can accurately locate the fault feeder with distorted information.The simulation results show that the rotation angle strategy and the complexity of distribution network have great influence on the fault location method proposed in this paper.Comparing the improved QGA with the standard genetic algorithm,the results show that the improved QGA has fast convergence speed,short running time and shorter searching time for fault location.