Research On Bi-level Programming Of Active Distribution Network Based On Improved Gray Wolf Algorithm

With the progress of human society,the traditional single energy network has been unable to meet the needs of production and life.The diversification of energy forms,more and more distributed generation accessed to distribution network,which are becoming more and more important for the rational allocation of distributed generation.How to establish a practical and effective mathematical model of distribution network planning is still a hot topic in the field of distribution network planning.In the system of distribution network planning,the intelligent algorithm with random search features shows better adaptability in solving this problem,which plays an important role in the speed and quality of optimization,and has good convergence characteristics.Therefore,this thesis deeply studies the problems and methods of distribution network planning in order to obtain effective optimization effects,so as to reduce the system network loss,improve the voltage level and improve the operation economy of distribution network.The main work of this thesis is as follows:In this thesis,the status of distribution network planning is analyzed first,and the distribution network planning method is studied in depth.With the analysis of different voltage sensitivity between different load buses for distributed generation access,an optimization model based on node voltage sensitivity is proposed on the traditional distributed generation siting and sizing model.The penalty function is applied to deal with the problem of node voltage crossing,branch current crossing and the distributed generation capacity crossing,which improves the adaptability of the model and application of improved algorithm for location selection and capacity determination of distributed generation.Secondly,this thesis deeply studies the application of Grey Wolf algorithm in the siting and sizing of distributed generation.Aiming at the disadvantage that Grey Wolf algorithm can easily converge to the local optimal solution,this thesis proposes an improved scheme for hunting target selection and the convergence factor of Grey Wolf algorithm.In the target selection,a threshold value is introduced to modify the target selected in the original algorithm to a target that exceeds the threshold value.The improved algorithm is applied to select the location of distributed generation and determine the capacity,while the simulation results show that the proposed model and the improved algorithm are feasible in the selecting location of distributed generation and determining the capacity.Finally,on this basis,we expand the planning research of the distribution network grid,and propose a bi-level programming model,grid planning in the upper layer,while selecting the location of distributed generation and determining the capacity in the lower layer.As the grid expansion planning is a discrete problem,this thesis proposes a binary improved gray wolf algorithm.The calculation formula of the original algorithm is mapped to 0-1 interval through a function,so as to solve the discrete problem of extended programming,and the feasibility of the bi-level programming model is verified by simulation.The simulation results are compared with the binary particle swarm optimization algorithm.The results show that the economy and power quality of the system are greatly improved after the binary improved gray wolf algorithm is optimized,which shows that the proposed planning model and algorithm are effective and reasonable.