System-Level Impacts of Flexible Data Center Load Scheduling on Cost, Emissions, and Transmission Congestion

TL;DR

This study examines how flexible data center load scheduling can reduce costs, emissions, and congestion in power grids without affecting latency-critical workloads, using a large test system.

Contribution

It provides system-level analysis of flexible data center load scheduling impacts on cost, emissions, and congestion, highlighting environmental and operational benefits.

Findings

BE loads shift to lower LMP periods, often with more renewables

Latency-critical workloads remain unaffected, maintaining QoS

Scheduling reduces emissions and transmission congestion

Abstract

Large data centers are being deployed in the U.S. at an unprecedented rate, introducing significant flexible load potential. A portion of data center workloads - best-effort (BE) jobs - can be scheduled flexibly to reduce power system operating costs and emissions. However, the system-level impacts of such scheduling remain underexplored. This paper investigates the effects of flexible data center load scheduling on operating cost, system stress, and emissions using the ACTIVSg2000 2000-bus test system. Results show that BE loads shift toward periods of lower locational marginal prices (LMPs), typically aligned with high renewable generation. Importantly, latency-critical (LC) workloads remain unaffected, preserving quality of service (QoS). Flexible scheduling also leads to reductions in both greenhouse gas and toxic emissions, as well as transmission congestion, compared to inflexible operation, demonstrating its potential to support more efficient and sustainable grid operation.