Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Optimal County-Level Siting of Data Centers in the United States

Maria Vabson, Muhy Eddin Zater, Amir Sajadi, Kyri Baker, Bri-Mathias Hodge

TL;DR

This study addresses the holistic siting of data centers by developing a county-level capacity-expansion optimization that simultaneously accounts for collocated generation, storage, transmission, fiber optics, and water use. The approach integrates a modular objective with horizon-dependent costs, using $Y$ years and a capital recovery factor $\rho$, to minimize total life-cycle costs while meeting hourly data-center demand $D^p_h$ through a mix of renewable and dispatchable resources. Key findings show that while capital costs dominate, extending the planning horizon and increasing collocated renewable energy and storage can shift siting toward regions with higher renewable potential and reduce overall costs; base-case results indicate southern and eastern counties may be more economical due to solar potential, and correlations highlight the role of geothermal and other factors in cost drivers. The framework offers a flexible tool for national-scale siting decisions and can be extended to include additional factors such as land, labor, and natural hazards to further inform sustainable infrastructure deployment.

Abstract

Data centers are growing rapidly, creating the pressing need for the development of critical infrastructure build out to support these resource-intensive large loads. Their immense consumption of electricity and, often, freshwater, continues to stress an already constrained and aging power grid and water resources. This paper presents a comprehensive modeling approach to determine the optimal locations to construct such facilities by quantifying their resource use and minimizing associated costs. The interdisciplinary modeling approach incorporates a number of factors including the power grid, telecommunications, climate, water use, and collocated generation potential. This work establishes the base model whose functionality is shown through several test cases focusing on carbon-free generation collocation on a county-level in the United States. The results suggest that while capital costs are the biggest driver, having a longer future outlook and allowing more variable generation collocation influences the model to choose sites with higher renewable potential.

Optimal County-Level Siting of Data Centers in the United States

TL;DR

This study addresses the holistic siting of data centers by developing a county-level capacity-expansion optimization that simultaneously accounts for collocated generation, storage, transmission, fiber optics, and water use. The approach integrates a modular objective with horizon-dependent costs, using years and a capital recovery factor , to minimize total life-cycle costs while meeting hourly data-center demand through a mix of renewable and dispatchable resources. Key findings show that while capital costs dominate, extending the planning horizon and increasing collocated renewable energy and storage can shift siting toward regions with higher renewable potential and reduce overall costs; base-case results indicate southern and eastern counties may be more economical due to solar potential, and correlations highlight the role of geothermal and other factors in cost drivers. The framework offers a flexible tool for national-scale siting decisions and can be extended to include additional factors such as land, labor, and natural hazards to further inform sustainable infrastructure deployment.

Abstract

Data centers are growing rapidly, creating the pressing need for the development of critical infrastructure build out to support these resource-intensive large loads. Their immense consumption of electricity and, often, freshwater, continues to stress an already constrained and aging power grid and water resources. This paper presents a comprehensive modeling approach to determine the optimal locations to construct such facilities by quantifying their resource use and minimizing associated costs. The interdisciplinary modeling approach incorporates a number of factors including the power grid, telecommunications, climate, water use, and collocated generation potential. This work establishes the base model whose functionality is shown through several test cases focusing on carbon-free generation collocation on a county-level in the United States. The results suggest that while capital costs are the biggest driver, having a longer future outlook and allowing more variable generation collocation influences the model to choose sites with higher renewable potential.
Paper Structure (23 sections, 19 equations, 5 figures, 2 tables)

This paper contains 23 sections, 19 equations, 5 figures, 2 tables.

Table of Contents

  1. Nomenclature
  2. Indices
  3. Parameters
  4. Demand Parameters
  5. Collocated Plant Parameters
  6. Additional Collocated Plant Parameters
  7. Storage Parameters
  8. Network Parameters
  9. Water Parameters
  10. Decision Variables
  11. Introduction
  12. Model Formulation
  13. Load Model
  14. Objective Function
  15. Collocated Generation Model
  16. ...and 8 more sections

Figures (5)

  • Figure 1: Model flow chart.
  • Figure 2: Hourly Generation Dispatch for Base Case
  • Figure 3: Heat Map Based on Optimization Objective for Base Case.
  • Figure 4: Pearson Correlation for Base Case.
  • Figure 5: The overall cost depending on allowable VG collocation (left, blue). The amount of VG utilization related to the amount of allowable VG collocation (right, green).