Microgrid Self-healing Control of Distributed Power Supply Combining Particle Swarm Optimization Algorithm

Microgrid is an important part of smart grid, and self-healing is a key feature of smart grid. The purpose of this paper is to combine the particle swarm optimization algorithm and the binary particle swarm optimization algorithm to study the self-healing control of the distributed power supply in the microgrid. Can be used to solve nonlinear multi-objective optimization problems with continuous and discrete variables. At the same time, considering the load shedding effects of fault recovery, switch opening and closing times, active and reactive power losses, node voltage drift, distributed generator performance, etc., it becomes a nonlinear, multi-objective function involving continuous or discrete variables.. After the optimal operation of the traditional microgrid system, the power factor and line loss cannot reach the optimal state. The line loss of microgrid 1 is 0.71, the power factor is 0.88, the line loss of microgrid 1 is 0.72, and the power factor is 0.88. In the plan, plan 1 operates the switch 2 times, plan 2 operates 5 times, and finally choose plan 1 with fewer operations.