Multi-Stage Operational Resilience Metric-Driven Optimal Service Restoration in DER-Rich Power Distribution Systems

The increasing occurrence of high probability events and the absence of a universal resilience metric have shifted the research paradigm towards quantifying resilience to support adaptive restoration. Thus, there is a need for a resilience-driven strategy for effective operation encompassing an immediate restoration in uncertain scenarios. However, distributed energy resources (DERs) have emerged as a crucial element for resilient distribution systems, but their integration introduces greater variability in operational decision-making. This paper proposes a novel integrated resilience assessment metric (IRAM) to support real-time operations in DER-rich distribution systems. This multi-stage metric significantly contributes in developing a formal resilience-driven solution in evolving distribution grids. The proposed metric utilizes pairwise criteria weights for resilience computation based on comprehensive attributes- operational redundancy, operational flexibility, and topological robustness. It plans for DER services by considering their operation and control modes, and real-time weather-dependent availability. The developed algorithm uses iterative meta-heuristic optimization to scan the system at different intervals and yield the optimal resilience-driven post-event restorative measure on observing the path redundancy. This work also utilizes weighted graph theory to compute the centrality indices, maintaining an efficacious level of robustness. The effectiveness of the proposed approach is validated through rigorous case studies on the IEEE-33 bus distribution system with 285 control variables optimizing for switching, load management, control strategies, and operational modes. Detailed results demonstrate that the developed approach maximizes the distribution system’s resilience by achieving 97% restoration amid extreme events.