Multi-objective Distribution Network Reconfiguration Based On Hybrid Gemini Group Algorithm

Due to the scarcity of traditional fossil energy,the development of renewable energy has attracted lots of attention in recent years.Reconfiguration of distribution network with distributed generation based on renewable energy is of great significance to improving operational efficiency and achieving energy conservation & emission reduction.In this paper,the particle swarm optimization and artificial bee colony algorithms were used to analyze the reconfiguration of distribution network with distributed generation.The paper contained the following:Firstly,the research background,importance and the current situation of distribution network reconstruction were briefly summarized.Secondly,the differences in power distribution were introduced.The power distribution calculated the energy distribution patterns that have identified different energy types.In order to simplify the calculation,the power source was treated as a node PQ in this paper.Distributed access would have a greater impact on the energy flow and voltage efficiency of the distribution network.Thirdly,the basic principle of particle swarm optimization and artificial bee colony algorithms was introduced.In view of the advantages and disadvantages of the two algorithms,a hybrid algorithm based on the twin sub-groups of artificial swarm was proposed to improve local search and global search performance through the twin sub-group information exchange mechanism.Through the selection of improved strategies,the bee colony's choice of honey source changed dynamically with evolution.Other strategies like dynamic inertia weight particle swarm optimization significantly improved the algorithm's local search performance.The accuracy of the improved artificial bee colony optimization algorithm was determined by the results of the optimized calculation.Finally,a multi-objective integrated mathematical model for reconfiguration was established to minimize system active loss,maximize distributed generation consumption,and minimize voltage deviation.The multi-objective function transformed and combined using the weighted minimum mode ideal point method effectively solved the problem of inconsistent dimensionality between sub-objectives,and further avoided solution deviation caused by the human factors during the dimensional conversion.A multi-objective integrated mathematical model for reconfiguration considering distributed generation consumption was established to effectively guarantee the diversified integrated objectives through the form of random weights.Decimal coding could simplify the reconfiguration model better,analyze homeomorphism graph and T node degree,which would avoid infeasible solutions.The analysis results of the actual calculation have shown that,in consideration of distributed generation consumption,the network reconfiguration enabled better voltage distribution and less system losses,providing reference for the actual operation of the distribution network with distributed generation.