Study On Distribution Network Reconfiguration Based On Interval Particle Swarm Optimization Algorithm

With the rapid development of the global economy,users have also put forward higher requirements on power supply and power supply quality.The reconstruction of the distribution network can improve the distribution system and increase the efficiency of the distribution network.It is possible to increase the efficiency,quality and reliability of the power grid without adding new equipment.Using intelligent algorithms can effectively find the optimal distribution network reconfiguration strategy.This paper proposes an interval particle swarm hybrid algorithm(IPSO)based on the characteristics of strong global search capability of interval optimization algorithm(IA)and fast convergence speed of particle swarm optimization algorithm(PSO).When judging the connectivity of the topological structure of the distribution network,an improved topology determination method is used to quickly determine whether the network is connected or not through less calculations.In the distribution network load flow calculation,considering the topology structure of the network,an improved forward push back generation method is selected,which has a good adaptability in the process of frequent network structure reconstruction.When using the interval particle swarm optimization algorithm to reconstruct the distribution network,the loop-based decimal encoding method is used,and the encoding length is significantly reduced compared to the binary encoding method,and the conversion process using the hybrid encoding is also avoided.In addition,when trying to improve the optimization efficiency of the algorithm,the principle of homeomorphograms is used to simplify the network,and two conditions that the feasible solution must satisfy are obtained,which facilitates the judgment of infeasible solutions and further reduces the calculation amount.Finally,with the goal of minimizing the loss of the distribution network,the IEEE33 node distribution network was reconstructed and compared with the effects of other algorithms.It can be seen that the selection interval particle swarm algorithm has significant characteristics in convergence efficiency and comprehensive optimization.