Optimal Scheduling of Data Centre Integrated Energy Systems Considering Electric‐Thermal Demand Response Under Icing Uncertainty

Extreme icing disasters increasingly undermine the reliability of integrated power and heat networks by causing line outages, supply shortages and sharp thermal load fluctuations. To address these challenges, this paper proposes a comprehensive optimisation framework that exploits the spatiotemporal flexibility of data centres for coordinated electric–thermal demand response under uncertain icing disasters. An improved spatiotemporal inverse distance weighting method combined with a Gaussian copula is first developed to reconstruct the joint spatial temporal dependence of icing variables, whereas a cellular automaton is introduced to capture icing‐driven fault propagation and generate representative stochastic scenarios. Based on these scenarios, an integrated electric–thermal demand response model is formulated, jointly leveraging data centre load migration and waste heat recovery, with an objective function incorporating operating cost, response benefits, icing‐related damage and social penalties. A case study in Chun'an County, Zhejiang Province, validates the proposed framework. Compared with fixed icing assumptions and decoupled power–heat scheduling, the method reduces residential electricity load shedding to 36.34%, increases data centre task migration utilisation to 67.21% and improves waste heat recovery efficiency to 73.45%. The results demonstrate that data centre flexibility can significantly enhance the resilience and reliability of multi‐energy systems under extreme icing disasters.