Data Center Spatio-Temporal Load Flexibility in Security-Constrained Unit Commitment for Enhanced Grid Efficiency and Reliability
Haoxiang Wan, Xingpeng Li

TL;DR
This paper introduces a modular MILP framework for coordinating data center workloads with grid operations, significantly improving renewable utilization and reducing congestion and costs.
Contribution
It develops a joint spatio-temporal flexibility model for data centers integrated into security-constrained unit commitment, enhancing grid efficiency and reliability.
Findings
DC-ST eliminates all transmission violations at 40% flexibility.
Renewable curtailment reduced by up to 84.4%.
Moderate flexibility levels of 20-30% capture most benefits.
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…
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