Abstract

Data center electricity consumption reached 4.4% of U.S. total in 2023 and is projected to grow to 6.7–12% by 2028, imposing increasing stress on transmission networks while representing a largely untapped source of controllable demand-side flexibility. This paper proposes a modular security-constrained unit commitment (SCUC) framework that coordinates flexible data center workloads with system-level scheduling to reduce renewable curtailment, alleviate congestion, and lower operating costs. Three mixed-integer linear programming (MILP) models are formulated: the Data Center Spatial model (DC-S), enabling instantaneous workload redistribution across geographically distributed sites; the Data Center Temporal model (DC-T), permitting each site to shift its deferrable load across time while preserving the daily energy balance; and the Data Center Spatio-Temporal model (DC-ST), jointly activating both mechanisms and spanning the largest feasible operating region. Case studies on a modified IEEE 24-bus reliability test system show that DC-ST eliminates all base-case and post-contingency transmission violations at a flexibility ratio of 40%, and reduces renewable curtailment by up to 84.4% at 30% relative to the inflexible baseline. Sensitivity analysis further reveals that moderate flexibility levels of 20%–30% already capture most of the achievable benefits, supporting practical deployment with limited operational burden on data center operators.

Index Terms

Data center load flexibility, security-constrained unit commitment, renewable curtailment reduction, transmission congestion relief, spatiotemporal workload scheduling, demand side resource, renewable energy integration.

Cite this paper:

Haoxiang Wan and Xingpeng Li, “Data Center Spatio-Temporal Load Flexibility in Security-Constrained Unit Commitment for Enhanced Grid Efficiency and Reliability”, IEEE IAS Annual Meeting, Vancouver, Canada, Oct. 2026.