Multi-objective Particle Swarm Optimization for Comparison of Optimal Distribution Grid Reconfiguration Tasks

Regarding the increasing share of distributed renew-able energy sources, distribution network reconfiguration (DNR) becomes more prominent. Due to nonlinear power flow equations and binary variables representing switching states, the DNR becomes a mixed integer nonlinear optimization problem. In this paper, we present a multi-objective approach using a particle swarm optimization for the DNR problem and compare different objective functions which are key aspects for distribution grid operators. A case study conducted on a real medium-voltage grid in Germany shows that DNR can significantly reduce energy exchange with the high-voltage grid, particularly when local generation exceeds local demand.