Dynamic Reconfiguration Of Active Distribution Network Based On Krill-Herd Algorithm

In recent years,the distributed energy resources including wind power generation,photovoltaic power generation and electric vehicles have attracted widespread attention due to their advantages such as reproducibility,cleanliness and economy.However,the load of distributed generations and electric vehicles is random and dispersive,which is difficult to predict.Large-scale distributed energy resources will affect the security,stability and power supply reliability of distribution network.Based on these features of load,the rational dynamic reconfiguration of the active distribution network can make the distribution network actively adapt to the requirements of distributed energy resources,which can not only reduce the cost of electricity,improve the installed capacity and efficiency of distributed generations,but also ensure the safety and stability of distribution network.Considering the operating characteristics of active distribution network and the load characteristics of distributed generations and electric vehicles,this thesis studies the dynamic reconfiguration of active distribution network based on kill-herd algorithm.The power flow calculation model of distributed energy sources and the power flow calculation methods of active distribution network were researched.The reconfiguration model of active distribution network considering network invulnerability was constructed.The distributed energy resources were simplified by converting DG node types.A method for simplification of topology based on minimum contact-loop matrix was proposed to avoid the infeasible solutions.A reconfiguration scheme of active distribution network based on a new heuristic algorithm—krill-herd algorithm was proposed.The simulation for the traditional distribution network,the active distribution network in normal operation,and the active distribution network in the fault state were analyzed.The time-load probability models of the photovoltaic power generation,wind power generation and electric vehicles were built.The Monte Carlo Method was used to simulate the load conditions of active distribution network and draw the daily load curve.The mathematical model that the time petiod can be divided according to the load conditions of active distribution network was constructed,and solved by CLARANS clustering algorithm.A method of calculating the node cost based on gray relational analysis theory to CLARANS clustering algorithm was proposed,which improves the calculate dimension and efficiency of CLARANS clustering algorithm.Took the status with similar load characteristics of distribution network into the same category,and indicated the load condition of this category by cluster centers to get the optimal solution in one day.Taking the life of switch and network loss into account,the krill-herd algorithm for the reconfiguration of active distribution network was improved in view of the characteristics of active distribution network and krill-herd algorithm.The improved krill-herd algorithm was applied to dynamic reconfiguration of active distribution network.The optimization capabilities of the improved krill-herd algorithm and the original krill-herd algorithm were compared,and a simulation analysis was performed for two situations of electric vehicles:do not consider the load regulation strategy and consider the intelligent regulation strategy in active distribution networks.Take the IEEE33 nodes distribution system,PG&E69 nodes distribution system and typical power distribution system in Taiwan Power Company as examples,which contain distributed energy resources.The simulation results indicate the proposed dynamic reconfiguration method to active distribution network has the advantages of avoiding infeasible solutions,fast convergence,and powerful global optimization ability,which has a high practical value.It has certain theoretical significance and practical value to construct a safe,economical and reliable active distribution network.