AI-Driven Energy and Power Systems for Intelligent, Resilient and Sustainable Energy Futures
Deadline for manuscript submissions: 30 April 2027.
Guest Editor (1)
Dr. Elkhatib Kamal
Laboratoire des sciences du numérique de Nantes (LS2N), École Centrale de Nantes, Nantes 44300, France
Interests:Artificial Intelligence for Energy Systems; Smart Grid Technologies; Power System Optimization and Control; Renewable Energy Integration; Energy Storage Systems; Machine Learning Applications in Power Systems; Energy Data Analytics; Distributed Energy Resource Management; Digital Twin for Energy Systems; Cyber-Physical Energy Infrastructure
The global transition toward sustainable, resilient energy infrastructure is accelerating the transformation of conventional power systems into highly interconnected, data-rich, and adaptive smart energy ecosystems. In this context, recent advances in Artificial Intelligence (AI) and Machine Learning (ML) are reshaping the planning, operation, control, and optimization of modern energy and power systems. These technologies enable enhanced situational awareness, predictive analytics, autonomous decision-making, and intelligent coordination across generation, transmission, distribution, storage, and consumption layers.
AI-driven approaches are becoming essential for managing the increasing penetration of renewable energy sources, distributed energy resources, electric vehicles, and flexible demand-side participation within modern Smart grids. Furthermore, emerging paradigms such as digital twins, edge intelligence, energy big-data analytics, and cyber-physical system integration are unlocking new opportunities for real-time system optimization and resilience enhancement under uncertainty and complex operational constraints.
This Special Issue aims to provide a high-impact platform for researchers, engineers, and practitioners to present cutting-edge advances, innovative methodologies, and interdisciplinary applications of AI technologies in energy and power systems. Contributions addressing theoretical developments, practical implementations, system-level demonstrations, and policy-relevant insights are particularly encouraged. By bringing together diverse perspectives from academia and industry, the Special Issue will highlight transformative AI-enabled solutions supporting the evolution of intelligent, secure, efficient, and sustainable energy infrastructures worldwide.
Potential topics include, but are not limited to:
AI-based power system operation, control, and optimization
Machine learning for renewable energy forecasting (solar, wind, hybrid systems)
Deep learning techniques for load prediction and demand response
AI-enabled distributed energy resource management
Intelligent energy storage modeling, control, and scheduling
Digital twin technologies for smart energy systems
Edge computing and distributed intelligence for grid-edge applications
AI for resilience enhancement and fault detection in power networks
Cybersecurity frameworks using AI for critical energy infrastructure
Multi-energy system coordination using intelligent optimization methods
AI-driven electric vehicle charging infrastructure integration
Energy big-data analytics and predictive maintenance strategies
Explainable AI for power system decision support
Hybrid physics-informed and data-driven energy system modeling
AI applications in energy markets and flexibility services
Socio-economic and policy implications of AI adoption in energy systems
