Sponsored by U.S. Department of Energy (DOE)

Data center

We developed an open-source, free software package (see the following links) which provides practical, end-to-end (from the IT equipment to heat rejection to the ambient) modeling and optimization for data center cooling. It can be used as a stand-alone tool by data center designers, service consultants and facility managers, or be integrated into existing data center management software for autonomous optimal operation. It will be the first practical tool that couples the modeling of airflow-management and cooling systems to enable a global data center cooling optimization. Its self-learning regression model enabled by an in situ adaptive tabulation algorithm and a fast fluid dynamics model can predict the critical airflow information under various operational conditions within a few milliseconds. The equation-based modeling language allows a fast and flexible modeling of various cooling system configurations. We will demonstrate the usage of our tool at two data centers located in two different climate zones.

Open Source Modelica Models for Data Center Cooling

This project has resulted in open source Modelica models for the data center cooling system. The models haven been released as a part of the DOE's open source Modelica Buildings library: http://simulationresearch.lbl.gov/modelica/releases/latest/help/Buildings_Applications.html#Buildings.Applications

The model development branch is at https://github.com/lbl-srg/modelica-buildings/tree/master/Buildings/Applications

Technical Advisory Group For The Project

Name Institution
Amistadi, Henry R. MITRE Corporation
Cleaver, Donald Keystone Critical Systems & Advisors
Doppelhammer, F. James University of Miami
Geraghty, Edward P. CEC Group, LLC
Groenewold, John JPMorgan Chase & Co.
Kaiser, Raymond Amzur Technologies
Meneghan, Brian W. Carrier Corporation
Plamondon, David University of Massachusetts Medical School
Sartor, Dale Lawrence Berkeley National Laboratory
Sorell, Vali Syska Hennessy Group, Inc.
Magnus Herrlin Lawrence Berkeley National Laboratory


Press Release