Guest Editors
Assoc. Prof. Yonis Gulzar
Email: ygulzar@kfu.edu.sa
Affiliation: Department of Management Information Systems, College of Business Administration, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
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Research Interests: AI in power systems, active distribution networks, smart grids, microgrids, DER integration, grid resilience, fault detection, energy management systems, forecasting, optimization
Assoc. Prof. Uzair Aslam Bhatti
Email: uzair@hainanu.edu.cn
Affiliation: School of Information and Communication Engineering, Hainan University, Haikou, 570100, China
Homepage:
Research Interests: active distribution networks, smart grids and microgrids, DER integration, distribution system planning and operation, grid resilience and reliability, power system optimization
Summary
The increasing penetration of distributed energy resources, electric vehicles, and flexible loads is transforming traditional distribution networks into highly complex and data-rich cyber-physical systems. Ensuring reliable, efficient, and resilient operation of these active distribution systems under uncertainty requires intelligence beyond conventional model-based methods. Artificial intelligence (AI), machine learning, and advanced data-driven techniques are emerging as key enablers for next-generation distribution network monitoring, control, and decision support.
This Special Issue focuses on AI-enabled approaches for resilient distribution networks and active distribution systems. It aims to bring together recent advances in machine learning, deep learning, reinforcement learning, and hybrid AI-optimization techniques applied to distribution system planning, operation, and protection. Suggested themes include (but are not limited to):
· Intelligent fault detection and localization
· Predictive maintenance of distribution assets
· Self-healing and resilient control strategies
· Load and renewable generation forecasting
· AI-based optimal power flow and decision support
· Voltage and frequency control in active distribution systems
· Network reconfiguration and resilience enhancement
· Real-time energy management of microgrids and distributed energy resources
· Uncertainty modeling and handling in distribution networks
· Explainable AI and trustworthy decision-making
· Digital twins for distribution systems
· Cyber-physical security of active distribution networks
By highlighting innovative AI-driven methodologies, practical implementations, and real-world case studies, this Special Issue seeks to advance the role of artificial intelligence in enabling resilient, autonomous, and sustainable distribution energy systems and to identify future research directions for intelligent power distribution infrastructures.
Keywords
artificial intelligence in power systems, active distribution networks, smart grids, machine learning, grid resilience, microgrids, distributed energy resources, energy management systems
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