Physics-Informed AI for Resilient Low-Carbon Energy Systems

Low-carbon energy systems are becoming increasingly complex due to high penetrations of renewable energy, distributed resources, and cyber-physical interactions. While traditional physics-based models offer interpretability and robustness, they often struggle to scale and adapt under uncertainty. Conversely, purely data-driven AI approaches provide strong predictive capabilities but may lack generalization, transparency, and reliability under extreme or unseen operating conditions.Physics-informed AI has emerged as a promising paradigm that integrates physical laws, system constraints, and domain knowledge into data-driven learning and decision-making frameworks. By combining the strengths of physics-based modeling and artificial intelligence, these approaches enable more robust forecasting, optimization, and control, supporting resilient and low-carbon operation of modern energy systems.This Research Topic aims to bring together cutting-edge research on physics-informed, physics-aware, and hybrid AI methods for resilient low-carbon energy systems. We welcome contributions that advance modeling, forecasting, optimization, and control by explicitly embedding physical principles into AI frameworks, as well as studies that assess system resilience, robustness, and reliability under uncertainty. Both methodological innovations and practical case studies demonstrating real-world relevance are encouraged.Topics of interest include, but are not limited to:• Physics-informed and hybrid AI methods for energy and power systems;• Forecasting, optimization, and control of low-carbon energy infrastructures;• Resilience, robustness, and reliability enhancement under uncertainty;• Integration of renewable energy, energy storage, and flexible demand;• Distributed energy resource management and cyber-physical interactions. Topic editors: Xin Lu, Wenliang Yin, Yi Yang Source: https://www.frontiersin.org/research-topics/77937/physics-informed-ai-for-resilient-low-carbon-energy-systems