Quantum AI for Intelligent Energy Management in Smart Grids and Microgrids

The rapid evolution of energy systems toward decentralized, data-driven, and low-carbon operation has created new challenges in real-time optimization, intelligent control, and system coordination under uncertainty. At the same time, emerging paradigms such as quantum computing and advanced artificial intelligence are opening new possibilities for modeling complex energy interactions and improving decision-making performance beyond classical approaches.This Research Topic aims to bring together cutting-edge research at the intersection of intelligent energy management for smart grids and microgrids, artificial intelligence, and quantum-enhanced optimization and learning. The focus is on both theoretical advances and practical implementations that address real-world challenges in modern power systems, including microgrid coordination, demand response, energy trading, and efficient smart-grid operation.We invite high-quality original research and review articles on topics including, but not limited to:- AI-driven energy management and optimization in smart grids and microgrids- Quantum-inspired and quantum-native algorithms for smart grid and power system applications- Multi-agent reinforcement learning for distributed energy coordination- Energy-efficient machine learning and neuromorphic computing for edge and smart grid applications- Demand response, flexibility management, and energy trading mechanisms in smart grid environments- Robust and uncertainty-aware control in renewable-integrated systems- Scalable and privacy-preserving energy management architectures for smart grids Topic editors: Lilia Tightiz, Pierluigi Siano, Hyo-Sik Yang Source: https://www.frontiersin.org/research-topics/79976/quantum-ai-for-intelligent-energy-management-in-smart-grids-and-microgrids