Setting Value Optimization Of Inverse Time Overcurrent Protection In Distribution Network Based On Improved Graw Wolf Algorithm

Distributed generation technology can not only make up for the shortage of long-distance power transmission,but also reduce power transmission loss.However,a large number of Distributed Generation(DG)connected to the distribution network will change the original grid structure,and the power flow direction will also become uncertain.Once the distribution network fails,the protective relay cannot operate normally,leading to fault spread,affecting the stability of the grid operation,and in serious cases,the power system will be paralyzed on a large scale.Inverse time overcurrent protection has the characteristic of shorter protection action time for more severe faults,and can quickly remove faults in the event of severe faults in the distribution network.The original setting value of inverse time overcurrent protective relay is not applicable because DG is connected to the power grid.Aiming at the optimization setting problem of inverse time overcurrent protection setting value of distribution network with DG,this paper proposes an optimization algorithm of inverse time overcurrent protection setting value based on the improved gray wolf algorithm,which enables the inverse time overcurrent protection to act accurately and quickly when the fault occurs in the matching network with DG,and cut the fault.The main research content of this article is as follows:(1)Through nonlinear programming,the optimization of inverse time overcurrent protection settings is transformed into a nonlinear multi constraint objective optimization problem,and the objective function and constraint conditions of inverse time overcurrent protection are established.Considering the complex and highly correlated constraints of inverse time overcurrent protection,this paper introduces a static penalty function to handle the constraints.By punishing items that do not meet the constraint conditions,a novel optimization model for inverse time overcurrent protection in distribution networks is established,which includes a static penalty function and the total time of protection actions.(2)Considering the model solving problem of inverse time overcurrent protection,and the fact that the Grey Wolf algorithm is prone to falling into local optima,in order to avoid falling into local optima during the optimization process of the Grey Wolf algorithm,this paper introduces a proportional adjustment factor to change the proportion of global search and local search,and a floating factor to optimize the activity range of Grey Wolf individuals,and proposes an improved Grey Wolf algorithm to improve the convergence speed and accuracy of the Grey Wolf algorithm.(3)Combining the improved Grey Wolf algorithm with the inverse time overcurrent protection optimization model,a inverse time overcurrent protection setting optimization strategy based on the improved Grey Wolf algorithm is proposed.Taking IEEE 15 node distribution network as an example,the setting optimization strategy is simulated and analyzed to verify the superiority of the proposed method in this paper.