When the Extreme Events Hit – Rethinking Power System Resilience Through Meteorology, AI, Data Centers, and Beyond

Extreme weather events driven by climate change pose increasing threats to power system security, particularly in electricity systems with high penetration of renewable energy and growing dependence on digital infrastructure. This paper examines the challenges and opportunities of enhancing power system resilience against low‐probability but high‐impact events by integrating cross‐domain perspectives from meteorology, artificial intelligence (AI), communication networks, and data centres. We review how different categories of extreme weather affect generation, networks, loads, and cyber‐communication layers, and highlight limitations of existing resilience studies. Advanced AI techniques, including deep learning and deep reinforcement learning, are discussed as key enablers for scalable, adaptive, and time‐critical resilience enhancement. Furthermore, the emerging role of data centres is analysed, emphasising their dual nature as both stressors and flexible demand, local generation, and computational support. This work aims to provide insights into existing challenges and potential solutions for enhancing power system resilience amid energy transitions and digitalisation.