Towards an Efficient Self-Healing Strategy for Smart Grids

Power system restoration following a large-scale blackout remains a challenging task due to the need to rapidly re-establish service while maintaining operational feasibility. Although numerous restoration approaches have been proposed, many existing methods focus either on network sectionalization or restoration scheduling, with limited emphasis on restoration-oriented clustering strategies that combine island validation and similarity-based merging. This paper proposes a self-healing strategy for smart grids based on restoration island validation and Jaccard-distance-guided clustering. Following a blackout, the network is partitioned into islands that are evaluated according to predefined restoration criteria and progressively merged through a restoration-oriented decision process. The proposed approach aims to accelerate system recovery by enabling parallel restoration of validated islands while preserving restoration feasibility. The methodology is illustrated using the IEEE nine-bus system and evaluated on the IEEE 39-bus and IEEE 118-bus benchmark systems. The obtained results demonstrate the effectiveness of the proposed strategy in reducing restoration time and improving restoration efficiency when compared with reference approaches reported in the literature. The proposed framework provides a practical restoration-planning tool for large-scale power systems and constitutes a basis for future extensions incorporating renewable energy sources, energy storage systems, and dynamic operational constraints.