A Rapid Resilient Critical Load Recovery of Microgrid Network Using Floyd-Based Particle Swarm Optimisation

Extreme weather events pose a significant threat to customer safety by exacerbating the ageing and obsolescence of power distribution infrastructure, resulting in prolonged power outages and disruptions of critical services. Therefore, there is a pressing need for the rapid recovery of critical loads during disasters to strengthen the resilience of the distribution system. To this end, combining the theories of weighted average consensus (WAC) and particle swarm optimisation (PSO) based on Floyd algorithm, a rapid resilient critical load recovery architecture (RCLRA) with two-level architecture is proposed. At the consensus level, the WAC is employed to promptly detect and isolate the faulty nodes, maintaining the stability and reliability of the system. At the microgrid (MG) formation level, the PSO based on Floyd algorithm is introduced to optimise MG formations under the shortest path, thereby maximising the resilience of the grid recovery after malfunctions and ensuring the connectivity of critical loads. The simulations utilise a standard IEEE 123-node feeder comprising 5 distributed energy resources (DERs) and 11 critical loads. The results verify that the RCLRA can significantly enhances the resilience of the distribution system in terms of the reserve capacity of DERs, maximum weighted load loss rate, and relative load recovery rate.