Distribution System Reconfiguration using Multi-Stage Evolutionary Strategy for Constraints Satisfaction in Faulted Conditions

Abstract

When a constraint violation occurs due to adding a new load to distribution systems, it can be resolved by reconfiguring the distribution systems by changing the states of switches and/or by minimum necessary investment. However, it is difficult to reconfigure the distribution system while satisfying the constraints made more severe by the new load installation. To find distribution system candidates that satisfy the severe constraints, this paper propose a multi-stage constrained multiobjective evolutionary algorithm (CMOEA). The proposed CMOEA dynamically changes the selection pressure at each search stage for constraints in normal and fault states, and it efficiently finds distribution system candidates that satisfy the severe constraints. Furthermore, the proposed CMOEA equals the number of sections and minimizes the number of remote/manual switch replacements as much as possible. The effectiveness of the proposed CMOEA is verified by case studies using a large-scale distribution system model equipped with many manual and remote switches.