Waste-to-Energy-Coupled AI Data Centers: Cooling Efficiency and Grid Resilience

AI data center expansion is increasingly constrained by grid interconnection capacity, driven in part by electricity-intensive cooling demand. This paper evaluates a coupled Waste-to-Energy (WtE) and AI data center configuration in which low-grade WtE thermal output drives absorption cooling, displacing grid-supplied cooling electricity. The system is modeled as a transparent input–output boundary and benchmarked against a conventional grid-powered cooling baseline. Results show that net grid-capacity relief is governed by three first-order factors: cooling coverage of IT heat load, parasitic auxiliary power, and distance-dependent thermal delivery losses. These factors define a break-even siting corridor beyond which capacity benefits vanish. The analysis shows that WtE-driven cooling can reduce grid imports under realistic conditions, enabling tighter integration of energy-generation resources with data centers.