When Market Prices Drive the Load: Modeling, Grid-Security Analysis, and Mitigation of Data Center Workload Scheduling

TL;DR

This paper models and analyzes how geographically distributed data centers' workload scheduling, driven by electricity prices, impacts grid stability and proposes mitigation strategies to reduce risks.

Contribution

It introduces a detailed mixed-integer scheduling framework for market-driven data centers, incorporating QoS constraints and load-redistribution policies for grid impact mitigation.

Findings

Price-driven scheduling improves economic performance.

Such scheduling increases voltage-security risks and congestion.

Load-redistribution policies effectively curb extreme load shifts.

Abstract

Data centers (DCs) are emerging as large, geographically distributed, controllable loads whose participation in electricity markets can significantly affect grid operation, especially when cloud platforms shift workloads across sites to exploit energy-arbitrage opportunities. This paper analyzes and seeks to mitigate the grid impacts of geographically distributed multi-site DCs under exogenous electricity prices. It develops a detailed job-level scheduling framework for market-driven DCs, formulated as a mixed-integer model that preserves execution logic and captures a unified set of implementable control actions. It also incorporates service-side quality-of-service (QoS) constraints and penalty terms to improve fidelity. Case studies on a modified IEEE 14-bus system, complemented by a more realistic network based on Travis County, Texas, show that purely price-driven scheduling improves economic performance, but also increases voltage-security risk and congestion exposure by inducing localized demand concentration and sharp site-level load variation. To mitigate these effects, this work introduces load-redistribution policies that curb extreme load shifting and support grid operators in managing such conditions.