Coordinating multi-energy stations for climate-resilient district cooling: A computationally efficient optimization framework

Accelerating global warming is driving a steady rise in urban cooling demand, highlighting the urgent need for climate-resilient district cooling systems (DCSs). Interconnecting multi-cooling energy stations can enhance cooling system flexibility and resilience, but it also introduces strong thermo-hydraulic coupling, temporal dependence of thermal storage, and high computational complexity. To address these challenges and enhance climate resilience, this study develops a computationally efficient optimization framework for the coordinated operation of multi-energy-station DCSs with hybrid water and ice thermal energy storage. The proposed model integrates a lossless network-reduction method and a high-precision spatiotemporal decomposition strategy to coordinate chillers, thermal storage, and cooling networks while maintaining hydraulic feasibility. Case studies based on a real DCS in Zhuhai, China, demonstrate that the proposed framework reduces energy consumption and operating costs by 5%–11%, increases effective cooling capacity by more than 16%, and achieves convergence within 5 min. Incorporating CMIP6-based climate projections, the proposed coordination delays the adequacy limit year, which is defined as the first year when peak demand exceeds available capacity, from 2028 2033 to beyond 2059, ensuring long-term operational adequacy under progressive global warming.