Dynamic Cluster Partition of Active Distribution Based on Sector Search Mode

In order to deal with the problem of difficult control and operation of a large number of distributed power sources, this study proposes a new sector search mode for dynamic cluster partition. Then, a multi-population quantum particle swarm optimization algorithm is proposed, which makes the top and bottom populations co-evolve, and the immigration operator bears the information interaction between populations, which improves the global search ability of particles and enhances the convergence accuracy of the algorithm. Finally, the modified PG&E 69 node system is used to verify the example. The results indicate that the improved algorithm has achieved a 7% increase in cluster power supply rate compared to the traditional algorithm, a 15.08% reduction in the required number of iterations for solution convergence, and, most importantly, a 1.12% improvement in the accuracy of solution distribution.