Decentralized parallel autonomous restoration: zone agents’ automated rules

• Decentralized methods enable fast, fully parallel restoration via structured zone agents. • Real-time rules enable automated, adaptive fault handling in predefined zones. • Super faults and tie switches streamline complex fault management for efficient restoration. • Consensus-based info matrix facilitates seamless global data exchange via zone agents. • Supports renewable integration, enhancing resilience while reducing costs. The ever-increasing demand for reliable, safe, and high-quality power has driven the development of autonomous smart distribution systems with self-healing capabilities. This study aims to develop a stable and autonomous framework to achieve simultaneous restoration within predefined zones. The framework incorporates the state-of-the-art decentralized mesh-based minimum spanning tree (DPMST) algorithm coordinated by zone agents, to enable concurrent recovery processes. It also leverages consensus negotiation and optimized topology to enable robust information exchange, granting access to global data for achieving a unified global solution. Additionally, it applies real-time rules within designated zones to facilitate automated, tailored responses for each region. The power grid is modeled as a network of edges and nodes, prioritizing restoration tasks with a specialized weight index. By employing the DPMST method, the simultaneous minimum spanning tree (MST) operation is efficiently executed in just a few steps. The islands are treated as unified entities by defining active and passive super faults and super tie switches, governed by automated rules. The framework minimizes the number of required agents and their collaboration and communication links, ensuring rapid restoration. Adaptability to the dynamic network is addressed. Simulations validate its effectiveness, scalability, and significant contribution to advancing resilient, sustainable smart grid systems.