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Enhancing Data Center Low-Voltage Ride-Through

Yiheng Xie, Wenqi Cui, Adam Wierman

TL;DR

The paper addresses LVRT for large data-center loads by exploiting the data center's internal distribution network and designing voltage controllers to keep internal voltages within safe limits during external grid disturbances, using a Linear DistFlow model $\mathbf{v}=\mathbf{R}\mathbf{p}+\mathbf{X}\mathbf{q}+v_0\mathbf{1}$. It compares centralized and decentralized control strategies for coordinating IT loads, cooling, UPS, and on-site storage to achieve stay-online operation. Key contributions include a systematic LVRT analysis for data centers, the development of centralized and decentralized voltage-control laws, and an open-source integrated test system for grid-data-center dynamics. The results demonstrate effective LVRT enhancement with practical implications for grid stability and data-center reliability.

Abstract

Data center loads have expanded significantly in recent years. Compared to traditional loads, data centers are highly sensitive to voltage deviations and thus their protection mechanisms trip more proactively during voltage fluctuations. During a grid fault, simultaneous tripping of large-scale data centers can further destabilize the transmission system and even lead to cascading failures. In response, transmission system operators are imposing voltage ride-through (VRT) requirements for data centers. In this work, we enhance the VRT capability of data centers by designing voltage controllers for their internal power distribution network. We first systematically analyze VRT standards and the controllable resources related to data centers. These resources enable the design of voltage control strategies to regulate voltages internal to the data center, thereby allowing loads to remain online during voltage disturbances from the external transmission grid. We study and contrast both centralized and decentralized controllers that unify the control of heterogeneous flexible resources. Additionally, we construct an integrated test system that simulates both the transient fault response of the transmission system and the data center distribution network. Case studies demonstrate that the proposed voltage control mechanisms provide effective yet simple solutions to enhance data center low-voltage ride-through capability.

Enhancing Data Center Low-Voltage Ride-Through

TL;DR

The paper addresses LVRT for large data-center loads by exploiting the data center's internal distribution network and designing voltage controllers to keep internal voltages within safe limits during external grid disturbances, using a Linear DistFlow model . It compares centralized and decentralized control strategies for coordinating IT loads, cooling, UPS, and on-site storage to achieve stay-online operation. Key contributions include a systematic LVRT analysis for data centers, the development of centralized and decentralized voltage-control laws, and an open-source integrated test system for grid-data-center dynamics. The results demonstrate effective LVRT enhancement with practical implications for grid stability and data-center reliability.

Abstract

Data center loads have expanded significantly in recent years. Compared to traditional loads, data centers are highly sensitive to voltage deviations and thus their protection mechanisms trip more proactively during voltage fluctuations. During a grid fault, simultaneous tripping of large-scale data centers can further destabilize the transmission system and even lead to cascading failures. In response, transmission system operators are imposing voltage ride-through (VRT) requirements for data centers. In this work, we enhance the VRT capability of data centers by designing voltage controllers for their internal power distribution network. We first systematically analyze VRT standards and the controllable resources related to data centers. These resources enable the design of voltage control strategies to regulate voltages internal to the data center, thereby allowing loads to remain online during voltage disturbances from the external transmission grid. We study and contrast both centralized and decentralized controllers that unify the control of heterogeneous flexible resources. Additionally, we construct an integrated test system that simulates both the transient fault response of the transmission system and the data center distribution network. Case studies demonstrate that the proposed voltage control mechanisms provide effective yet simple solutions to enhance data center low-voltage ride-through capability.

Paper Structure

This paper contains 28 sections, 2 theorems, 5 equations, 8 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Contributions
  3. Related Work
  4. Grid-friendly Data Centers
  5. Voltage Ride-through
  6. Voltage Control
  7. Challenge and Opportunity
  8. Voltage Ride-through Requirements
  9. Device Standards
  10. Grid Codes
  11. Controllable Devices within Data Centers
  12. IT Loads
  13. Cooling Loads & Thermal Storage
  14. Electrical Storage
  15. Backup Generation
  16. ...and 13 more sections

Key Result

theorem 1

Let $\bm{K}^p:=diag(k_1^p,\cdots, k_n^p)$ and $\bm{K}^q:=diag(k_1^q,\cdots, k_n^q)$ be the diagonal matrices formed by control gains in eq:decentralized_control. If the spectral radius of $\left(\bm{I}-\bm{R}\bm{K}^p-\bm{X}\bm{K}^q\right)$ is smaller than 1, then the voltage deviation $\tilde{\bm{v}

Figures (8)

  • Figure 1: Voltage ride-through requirement curves.
  • Figure 2: Data center and grid interconnection. For demonstration purposes, the transmission system is IEEE New England 39 bus test system, and the data center network is adapted from the Vulcan Test Platform in vaidhynathan_vulcan_2025.
  • Figure 3: Modeling the interactions between the transmission system and data centers.
  • Figure 4: Data cluster computing load (per cluster)
  • Figure 5: Data center voltages and load without voltage control.
  • ...and 3 more figures

Theorems & Definitions (2)

  • theorem 1: Convergence of voltage
  • theorem 2: Decentralized Stabilizing Conditions