Trustworthy, Explainable AI for Smart Grid Protection and Autonomous Operation

The increasing penetration of renewable energy resources, distributed energy systems, electric vehicles, and advanced sensing technologies has significantly increased the complexity of smart grid operation. Conventional model-based methods often struggle to cope with uncertainty and high-dimensional data, whereas purely data-driven approaches may lack transparency, robustness, and physical consistency. Recent advances in explainable AI, trustworthy machine learning, physics-informed learning, digital twins, and uncertainty-aware optimization offer promising pathways toward intelligent yet reliable power system operation. However, substantial challenges remain in translating these techniques into deployable solutions that satisfy operational requirements and stakeholder confidence.Modern smart grids are rapidly evolving toward highly decentralized, renewable-rich, and data-driven energy systems. While artificial intelligence has demonstrated remarkable capabilities in forecasting, optimization, protection, and decision support, concerns regarding reliability, interpretability, transparency, and trustworthiness continue to hinder large-scale deployment in critical power infrastructure.This Research Topic aims to advance the development and application of trustworthy, explainable, and physics-informed AI methodologies for smart grid operation. By bridging domain knowledge from power engineering with modern AI techniques, this collection seeks to improve the reliability, security, resilience, and acceptance of intelligent solutions in future energy systems. The Topic encourages interdisciplinary contributions that combine theoretical developments with practical validation and real-world applications.This Research Topic welcomes original research articles, review papers, methods papers, and case studies addressing, but not limited to:• Explainable and interpretable AI for power systems;• Physics-informed machine learning and hybrid modeling;• Trustworthy AI frameworks for smart grids;• AI-enabled protection and fault diagnosis;• Monitoring and condition assessment of grid assets;• Renewable energy forecasting and uncertainty quantification;• Autonomous operation of microgrids and distribution systems;• AI for resilience enhancement and restoration strategies;• Electric vehicle integration and energy management;• Cybersecurity and anomaly detection in smart grids;• Digital twins for intelligent grid operation;• Human-centered decision support and responsible AI deployment.Submissions involving real-world datasets, field demonstrations, benchmark studies, and reproducible methodologies are particularly encouraged. Topic editors: Duy C. Huynh, Nga Nguyen, Corina Barbalata Source: https://www.frontiersin.org/research-topics/82723/trustworthy-explainable-ai-for-smart-grid-protection-and-autonomous-operation