Application Of Time-varying Compression Factor Beetle Swarm Optimization In Distribution Network Fault Location Of Distributed Generation With Inverter

The function of fault location in distribution network is to locate the fault section accurately and timely,shorten the outage time of the fault section,and further improve the reliability of power supply.However,large-scale grid-connected distributed power supply has brought many problems while reducing the burden of peak load regulation in distribution network.The most direct problem is relay protection.When a fault occurs in distribution network,the current flowing through the fault point is no longer a single bus to the fault point,and the power may also be reversed.Furthermore,the traditional design and setting scheme of relay protection fault location in distribution network is no longer applicable,so it is particularly important to study a new fault location method for distribution network with distributed generation.Firstly,this paper analyses the impact of the inverted distributed generation on the protection of distribution network,and uses PSCAD/EMTDC to simulate and verify the above theory.Secondly,starting with the application of artificial intelligence algorithm in fault location method of distribution network based on FTU,the widely used and simple particle swarm optimization algorithm is selected as the research object,and the transmission method is used.The particle swarm optimization(PSO)method for fault location in distribution network is deeply studied in the aspects of mathematical model,binarization of algorithm,switching function and fitness function of fault location for single-source distribution network and distribution network with distributed power.The simulation examples of 20-node distribution network and 7-node distribution network with distributed power are given to verify the partition of PSO algorithm.The feasibility of fault location in distribution network with distributed power supply and the shortcomings and shortcomings of particle swarm optimization(PSO)in the application of distribution network faults.After that,this paper mainly aims at the problem that the standard particle swarm optimization(SPSO)algorithm is easy to fall into the local optimum when the number of nodes is large,and has the disadvantage of low accuracy of fault location.By introducing time-varying compression factor and combining with Longhorn whisker algorithm,a time-varying Longhorn swarm algorithm is mixed to improve the performance of particle swarm optimization.Four commonly used benchmark functions are used to verify the effectiveness and feasibility of the time-varying Longhorn swarm algorithm.At the same time,it is the first time to use "0.5 threshold" method to binary the time-varying day cow algorithm.Taking 33 node distribution network as an example,in the case of complete and partial distortion of fault information,MATLAB software is used to verify the high fault tolerance and reliability of the algorithm in the distribution network fault location with distributed power supply.Finally,by comparing with particle swarm optimization,longicorn swarm optimization,time-varying particle swarm optimization and simulated annealing particle swarm optimization,the simulation results show that the reliability and convergence of time-varying longicorn swarm optimization in fault location of distribution network with distributed generations are better than other algorithms tested.