Climate- and technology-specific PUE and WUE estimations for U.S. data centers using a hybrid statistical and thermodynamics-based approach

Overview

Data centres' on-site water use is becoming an important consideration for policy and energy analysis communities, but lack of operator-reported water usage effectiveness (WUE) values made it hard to quantify in macro-level models. The study fills this gap with thermodynamically compatible PUE and WUE values for a wide range of US data-centre archetypes and climate zones, using a physics-based model validated with real-world data. Archetypes cover size classes and cooling systems: airside economiser with or without adiabatic cooling, waterside economiser, water-cooled and air-cooled chillers and DX. Monte Carlo sampling of setpoints, equipment efficiencies and cooling-tower parameters gives ranges rather than single values.

Predicted median PUE ranges are 1.12-1.25 for large-scale data centres (cases 1-2), 1.39-1.98 for midsize (cases 3-7) and 1.71-2.22 for small (cases 8-10). The highest PUE generally occurs in climate zone 1A (hot moist) and the lowest in zone 8 (subarctic); airside-economiser-only cases have their lowest PUE in 4C (marine), and waterside-economiser cases in 3C.

Water-cooled chiller data centres with no economiser (cases 5 and 8) have the highest WUE because of cooling-tower water use. WUE falls only weakly in cooler climates because most rejected heat is the IT load itself, which does not depend on climate. Airside economisers with adiabatic cooling (case 1) use less water than airside economisers alone (case 3), because they reduce running hours of the more water-intensive supplemental cooling. Air-cooled chillers and DX systems have very small direct water use but are less energy-efficient, so their total footprint including indirect water may be significantly higher. WUE variance is largest for cooling-tower cases, with levers including more efficient chillers, windage drift eliminators and higher cycles of concentration within acceptable limits.

Limits: the facts reported come from the preprint version; the model is limited to US climate zones and ten archetypes, and results should be read as ranges and not transferred directly to other countries' climates and grids.

Key points

1. Predicted median PUE ranges: 1.12-1.25 for large-scale (cases 1-2), 1.39-1.98 for midsize (cases 3-7) and 1.71-2.22 for small (cases 8-10).
2. The highest PUE generally occurs in climate zone 1A (hot moist) and the lowest in zone 8 (subarctic); airside-economiser-only cases have their lowest PUE in 4C (marine) and waterside-economiser cases in 3C.
3. Water-cooled chiller data centres with no economiser (cases 5 and 8) have the highest WUE; WUE falls only weakly in cooler climates because most rejected heat is the climate-independent IT load.
4. Airside economisers with adiabatic cooling (case 1) use less water than airside economisers alone (case 3).
5. Air-cooled chillers and DX have very small direct water use but are less energy-efficient; their total footprint including indirect water may be significantly higher.
6. WUE variance is largest for cooling-tower cases; levers include more efficient chillers, windage drift eliminators and higher cycles of concentration within acceptable limits.

Using it in design

• In early data-centre design, set PUE and WUE targets by size class, cooling system and climate zone using this study's ranges (for example 1.71-2.22 for small rooms, 1.12-1.25 for large scale).
• For cooling-tower designs, evaluate more efficient chillers, drift eliminators and higher cycles of concentration as WUE levers.
• When choosing air-cooled chillers or DX, weigh low direct water use against the increase in energy and indirect water.

Who should read it

Energy analysts and designers modelling data-centre energy and water use by size, cooling system and climate.

Document contents

1. 1. Introduction
2. 2. Previous WUE analyses
3. 3. Methodology (3.1 Modeling scope and system definitions, 3.2 DC PUE and WUE model, 3.3 Model inputs and data sources, 3.4 Uncertainty and sensitivity analysis)
4. 4. Results and discussion (4.1 Model validation, 4.2 On-site PUE and WUE simulation results, 4.3 Climate dependent practical minimum PUE and WUE values, 4.4 Sensitivity analysis results)
5. 5. Conclusions

Related standards

• ASHRAE TC9.9 Thermal Guidelines
• ASHRAE 90.4
• ISO/IEC 30134-9 (WUE)

Read the document

Publication details

Authors

Nuoa Lei; Eric Masanet

Publisher

Resources, Conservation and Recycling (Elsevier BV)

Year

2022

Volume

182

Pages

106323

Document language

English

Source type

Scientific

Access

Open licence — downloadable

DOI

10.1016/j.resconrec.2022.106323

Licence

CC BY 4.0 — share with attribution

Licence evidence

www.researchsquare.com

Citation