Power System Stability and Intelligent Control

Dear Colleagues,

As modern power grids undergo a profound transformation driven by the large-scale integration of inverter-based resources (IBRs) and increasing system decentralization, traditional stability frameworks are reaching their limits. The transition from synchronous machine-dominated systems to low-inertia, converter-interfaced networks introduces complex dynamic behaviors, requiring new paradigms for monitoring, analysis, and control.

1. Focus, Scope, and Purpose

This Special Issue aims to bridge the gap between classical power system stability theory and modern computational intelligence. In particular, it explores how intelligent methods—ranging from decentralized control to advanced machine learning—can enhance the stability and resilience of next-generation power systems.

The scope includes, but is not limited to, the following:

• Stability Analysis: Small-signal and transient stability in low-inertia systems, including sub-synchronous oscillations and grid-forming (GFM) converter dynamics.
• Intelligent Control: Applications of deep reinforcement learning (DRL), robust control, and model predictive control (MPC) for real-time voltage and frequency regulation.
• Resilience and Protection: AI-based fault detection, wide-area monitoring systems (WAMS), and emergency control to prevent cascading failures.
• Hybrid Systems: Stability challenges in AC/DC integrated grids, microgrids, and multi-terminal HVDC systems

The purpose of this Special Issue is to provide a high-impact platform for interdisciplinary research that integrates power electronics, control theory, and data-driven methods.

2. Contribution to Existing Literature.

This collection complements the existing literature by addressing emerging challenges in inverter-dominated and data-driven power systems:

• Tackles the “black-box” challenge through explainable AI (XAI) and physics-informed approaches
• Investigates large-scale inverter–grid interactions, beyond individual device-level control
• Explores the integration of cyber–physical security into intelligent control frameworks

Dr. Phi Hai Trinh
Dr. Rehman Zafar
Guest Editors

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