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Building better energy models with the help of DOE supercomputers

Building better energy models with the help of DOE supercomputers

Researchers at the Department of Energy's Oak Ridge National Laboratory have developed open source software to help improve energy efficiency of residential and commercial buildings.

The Autotune code automatically calibrates building energy models with actual usage, which reduces the amount of time and expertise needed to optimize building parameters for cost and energy savings. It also increases the accuracy over current manual modeling calibration techniques.

To develop the software, the team used DOE supercomputing and computational resources -- including ORNL’s Titan supercomputer and the National Institute for Computational Sciences’ Nautilus system -- to perform millions of simulations for a range of standard building types.

On Titan, the team has been able to run annual energy simulations for more than half a million buildings and write 45 terabytes of simulation output to disk in less than one hour -- using just over a third of Titan’s nearly 300,000 CPU cores in parallel.

The Autotune code includes a backend that performs the evolutionary calibration, a web service that allows scripting for calibrating large numbers of buildings and a front-end website.

Autotune is available on GitHub.

Posted by GCN Staff on Sep 04, 2015 at 7:20 AM


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