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Research, white papers, reports, and presentations on data centers, energy, and modern infrastructure from around the world.

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480 V power distributionA/B testingAI data centersAI energy efficiencyAI factoriesAI infrastructureAI-based HVAC controlASHRAEAbsorption chillersBESSBMSChiller plantsCogenerationCombined CycleConcurrent MaintainabilityCorporate PPAsData center coolingData center energy consumptionData center power supplyData centersDirect Liquid CoolingEnergy consumption modelingEnergy efficiencyEngineering systems operationsFree cooling
Academic PaperDeepMind2022

Controlling Commercial Cooling Systems with Reinforcement Learning

A technical paper by DeepMind, Google, and Trane on controlling commercial-building chiller plants using reinforcement learning (RL). The authors describe BCOOLER, a system that generates safe recommendations for setpoints and equipment configurations based on BMS data, energy-use forecasts, and operating constraints. In real-world A/B experiments at two sites, the system reduced energy consumption by 9% and 13%, respectively, compared with Trane’s heuristic Sequence of Operations (SOO).

Reinforcement LearningAI-based HVAC controlChiller plantsData center cooling
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White PaperASHRAE2021

Emergence and Expansion of Liquid Cooling in Mainstream Data Centers

An ASHRAE technical white paper on the factors accelerating the transition of data centers from predominantly air-based to liquid cooling. The document links rising CPU, GPU, FPGA, and memory power levels to the limitations of air-based systems in terms of airflow, temperature, noise, rack density, and personnel safety. It examines ASHRAE water classes, direct liquid cooling and immersion cooling, and the implications for PUE, TCO, power delivery, heat reuse, and deployment in enterprise, HPC, and colocation data centers.

Liquid coolingDirect Liquid CoolingImmersion coolingData center cooling
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Government ReportLawrence Berkeley National Laboratory2016

United States Data Center Energy Usage Report

This Lawrence Berkeley National Laboratory study, supported by the U.S. Department of Energy’s Federal Energy Management Program, estimates energy use by U.S. data centers from 2000 to 2020. The model covers servers, storage systems, networking equipment, and facility infrastructure, using data on the installed base of IT equipment and PUE by facility type. The report compares the current trend with a counterfactual scenario in which 2010 efficiency levels are maintained, and examines the potential of improved management, best practices, and workload migration to hyperscale data centers.

Data center energy consumptionPUEHyperscale data centersEnergy efficiency
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