The transition toward net-zero carbon emissions and increasing demand for grid flexibility are accelerating the integration of renewable energy sources (RESs), energy storage systems, and power electronic converters in grid, leading to the emergence of power electronics-dominated grids (PEDGs). In parallel, the rapid expansion of artificial intelligence (AI) is driving the deployment of large-scale AI data centers (AI-DCs), introducing substantial, highly dynamic loads on the power grid. The increasing penetration of these emerging resources and loads is fundamentally changing grid dynamics and creating new challenges for maintaining system stability, reliability, resilience, and security.

High penetration of converter-interfaced resources, variable renewable generation, and dynamic AI-DC loads can increase grid sensitivity to disturbances, rapid generation-load variations, reduced system inertia, and complex interactions among grid-forming and grid-following converters. Furthermore, the increasing reliance on communication and coordinated control introduces additional cybersecurity vulnerabilities. Addressing these challenges requires advanced modeling, stability assessment, converter control and coordination, energy storage, demand-side flexibility, cyber-resilient control, and real-time monitoring and validation. Emerging technologies such as AI, machine learning, data-driven methods, and digital twins can further enhance intelligent control, dynamic security assessment, intrusion detection, and post-disturbance restoration.

Based on this vision, the proposed special session will provide a platform for researchers and industry experts to present emerging methodologies and technologies for the stable, resilient, reliable, and secure operation of future PEDGs with high penetration of RESs, energy storage, and AI-driven data centers.

• Resilient and adaptive control of converter-interfaced power systems
• Modeling and stability analysis of power electronics-dominated grids
• Grid-forming and grid-following converter control and coordination
• Grid integration and dynamic modeling of AI-driven data centers
• Cybersecurity and cyber-resilient control of power electronics-dominated grids
• AI, machine learning and data-driven methods for grid monitoring, control and stability
• Digital twins and real-time simulation of future power systems
• Hardware-in-the-loop and experimental validation of advanced grid control techniques
• Cryptography-based authentication and secure communication in power electronics-dominated grids
• Hardware-based security integration in power electronics-dominated grids