Distribution Network Reconfiguration Based On Improved Kruskal Algorithm And Reactive Power Optimization

With the improvement of people’s quality of life and standard of living, power user increasingly demanding the high-quality supply. In addition, with the deepening of demand side reform of electricity prices, the distribution network reliability and economy are increasingly high requirements. Research on distribution network reconfiguration problem is of great significance to improve the reliability and economy, including two aspects, on the one hand is the economic reconstruction of the distribution network, mainly to reduce distribution network losses problem; on the other hand is the fault of the power distribution network reconfiguration, recovery loss of power supply problems when the main troubleshooting areas. This article is for the economy to expand distribution network reconfiguration study.Net loss for the minimum objective function network topology problems, in this paper, this paper uses the improved Kruskal algorithm to obtain the minimum spanning tree. First, this paper uses the power flow calculation of the distribution network to obtain the node voltage of the system; Second, based on the network node voltage, the voltage balance coefficient is calculated to form the initial spanning tree. Finally, according to the specific structure of distribution network, through the improvement of objective function, and to meet certain constraints, repeat iteratively update the weights to select the optimal path, and get the optimal system network topology.In order to reduce the network loss and improve the voltage quality to improve the system power flow distribution, this paper uses the particle swarm optimization algorithm to optimize the reactive power. The initial power flow calculation for each particle fitness function using the network topology has been obtained, the optimal location and the global extreme population selection; storage of all particles within populations including the optimal choice by particles, so as to obtain another kind of group; the optimal location and the corresponding update all particles in the fitness function; sort according to the size of fitness, produce small particles is a new perturbed iterative optimal location and the optimal fitness function by particle, precision until the maximum number of iterations or given to the end of iteration and the optimal solution of reactive power optimization results of the network.Research of this paper, to reduce losses and improve the economic efficiency of enterprises and electricity users has practical significance.