Stability, Operation, and Control in Power Systems

Dear Colleagues,

With the rapid integration of renewable energy and smart grid technologies, modern power systems face unprecedented challenges in stability, operational efficiency, and control robustness. The traditional power system paradigm, which was designed for centralized generation and unidirectional power flow, is undergoing a profound transformation driven by the increased incorporation of variable renewable energy sources (VRESs), the proliferation of distributed energy resources (DERs), advanced metering infrastructure, and demand response programs. Furthermore, with the development of complex cyber–physical systems (CPSs), physical components, communication networks, and computational resources are deeply intertwined. This information–physical fusion has fundamentally transformed power system architectures, enabling real-time data exchange between generation, transmission, distribution, and consumption nodes—but simultaneously introducing unprecedented challenges in stability, operational efficiency, and control robustness.

Against this backdrop, artificial intelligence (AI) has emerged as a transformative force, redefining how power systems are monitored, analyzed, and controlled. Machine learning algorithms, deep neural networks, and reinforcement learning techniques are increasingly deployed to handle the massive data streams generated by smart meters, sensors, and IoT devices in cyber–physical power systems. These AI-driven solutions offer breakthrough capabilities in predicting renewable energy fluctuations, optimizing real-time power flow, detecting cyber–physical anomalies, and adapting control strategies to dynamic operating conditions.

This Special Issue invites original research addressing cutting-edge solutions for the following areas:

• ‌Stability enhancement‌ in high-penetration renewable scenarios;
• Cloud–edge–end collaboration for reliable power systems;
• Sensing–Communication–Computing–Control Integration;
• ‌AI-driven optimization‌ for grid operation and load balancing;
• ‌Resilience strategies‌ against extreme events (e.g., cyberattacks, natural disasters);
• ‌Decentralized control‌ of microgrids and distributed energy resources;
• Machine learning and artificial intelligence applications in power system operations;
• Robust control methods for dealing with uncertainties in renewable generation;
• Market mechanisms and their impact on power system operation and control;
• Power system planning considering stability and control requirements.

Dr. Wei Liu
Prof. Dr. Zhenyu Zhou
Guest Editors

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