Nuclear-driven integrated energy systems to enhance data center sustainability: Multi-objective optimization of energy scheduling, economic performance, and carbon footprint

The exponential growth of data centers (DCs) in the era of artificial intelligence is straining the energy sectors with increasing energy demands, posing challenges to the global energy transition. Small modular reactors (SMRs) offer a potential decarbonization option for energy-intensive industries. However, their deployment remains subject to economic viability and operational strategies. In the present work, an innovative nuclear-driven integrated energy system (NIES) was proposed for DCs. A two-stage hierarchical optimization framework was developed by integrating hybrid intelligent algorithms with a comprehensive evaluation model. Two novel strategies were evaluated under SMR constant-load constraints: nuclear-driven following electricity loads (N-FEL) strategy and nuclear-driven following cold loads (N-FCL) strategy. The results of a case study indicate that NIES achieved a cost advantage over the conventional integrated energy systems (CIES). The levelized cost of energy (LCOE) of NIES reached 61.73 $/MWh, which was 10.1% lower than the grid cost. For the NIES, the carbon emissions intensity (CEI) was obtained as 393 kg CO₂ eq/MWh, 20.12% lower than that of renewable-integrated energy systems (RIES). Furthermore, the LCOE under N-FCL strategy with absorption chiller priority was 55.59 $/MWh, reduced by 5.02% compared to that under the N-FEL strategy. Phased deployment of SMRs supported evolving DC loads by aligning capacity additions with demand growth, which reduced the LCOE by 12.9% compared with the lump-sum capacity expansion. Overall, the synergistic interaction between SMR stability and renewable energy intermittency was quantified, providing strategies to address energy challenges and enhance DC sustainability through low-carbon and reliable energy integration.