New software created by Oak Ridge National Laboratory (ORNL), the University of Tennessee and Jacksonville State University in Alabama is designed to eliminate a challenge in creating and using energy models for retrofit planning, retro-commissioning, and measuring and verifying building efficiency measures, such as would be needed to make decisions related to lighting system upgrades, HVAC equipment replacement, etc. The challenge has been to derive difficult-to-obtain model inputs, such as air infiltration rates, plug loads, degraded equipment efficiencies.
Until now, this has been done by calibrating against measured data, such as monthly utility bills, interval meter or sub-meter data, zone temperatures, or other sensor data streams. The problem has been that—during calibration—uncertain inputs must be experimentally varied until simulation outputs are deemed sufficiently close to measurements. In other words, the process has been manually intensive and time-consuming. Also, the human element has placed practical limits on the amount and accuracy of data that can be used during calibration.
The new software, Autotune, was largely funded by the U.S. Department of Energy. It is intended to speed up the process by reducing the demand on the user and increasing the capability of computing.
Autotune uses what the DOE’s Office of Energy Efficiency & Renewable Energy calls “evolutionary computation” to calibrate model inputs using any sources of measured data. Autotune has already demonstrated the ability to outperform manual calibration and exceed ASHRAE Guideline 14 calibration requirements within minutes. In fact, during field tests, Autotune was able to eliminate about 45 hours of manual calibration per building.
Recently, the ORNL created Tunation LLC, a startup company designed to bring Autotune to market, likely within a year.