Pareto Dominance-Based Multiobjective Optimization Method for Distribution Network Reconfiguration

With ever increasing deployment of automation and communication systems in smart grids, distribution network reconfiguration is becoming a viable solution for improving the operation of power grids. A novel hybrid optimization algorithm is proposed in this paper that determines Pareto frontiers, as the candidate solutions, for multiobjective distribution network reconfiguration problem. The proposed hybrid optimization algorithm combines the concept of fuzzy Pareto dominance with shuffled frog leaping algorithm (SFLA) to recognize optimal nondominated solutions identified by SFLA. The local search step of SFLA is also customized for power systems application so that it automatically creates and analyzes only the feasible and radial configurations in its optimization procedure, which significantly increases the convergence speed of the algorithm. Moreover, an adaptive reliability-based frog encoding is introduced that supervises the algorithm to concentrate on more reliable network topologies. The performance of the proposed method is demonstrated on a 136-bus electricity distribution network.