Evaluation of “Autotune” calibration against manual calibration of building energy models
Abstract
Our paper demonstrates the application of Autotune, a methodology aimed at automatically producing calibrated building energy models using measured data, in two case studies. In the first case, a building model is de-tuned by deliberately injecting faults into more than 60 parameters. This model was then calibrated using Autotune and its accuracy with respect to the original model was evaluated in terms of the industry-standard normalized mean bias error and coefficient of variation of root mean squared error metrics set forth in ASHRAE Guideline 14. In addition to whole-building energy consumption, outputs including lighting, plug load profiles, HVAC energy consumption, zone temperatures, and other variables were analyzed. In the second case, Autotune calibration is compared directly to experts’ manual calibration of an emulated-occupancy, full-size residential building with comparable calibration results in much less time. Lastly, our paper concludes with a discussion of the key strengths and weaknesses of auto-calibration approaches.
- Authors:
-
- Indian Ins., of Technology, Roorkee (India). Dept. of Architecture and Planning
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Univ. of Alabama, Tuscaloosa, AL (United States). Dept. of Mechanical Engineering
- International Inst. of Information Technology, Hyderabad (India)
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- OSTI Identifier:
- 1311239
- Alternate Identifier(s):
- OSTI ID: 1550719
- Grant/Contract Number:
- AC05-00OR22725; BT0201000; DEAC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Applied Energy
- Additional Journal Information:
- Journal Volume: 182; Journal Issue: C; Journal ID: ISSN 0306-2619
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 29 ENERGY PLANNING, POLICY, AND ECONOMY
Citation Formats
Chaudhary, Gaurav, New, Joshua, Sanyal, Jibonananda, Im, Piljae, O’Neill, Zheng, and Garg, Vishal. Evaluation of “Autotune” calibration against manual calibration of building energy models. United States: N. p., 2016.
Web. doi:10.1016/j.apenergy.2016.08.073.
Chaudhary, Gaurav, New, Joshua, Sanyal, Jibonananda, Im, Piljae, O’Neill, Zheng, & Garg, Vishal. Evaluation of “Autotune” calibration against manual calibration of building energy models. United States. https://doi.org/10.1016/j.apenergy.2016.08.073
Chaudhary, Gaurav, New, Joshua, Sanyal, Jibonananda, Im, Piljae, O’Neill, Zheng, and Garg, Vishal. Fri .
"Evaluation of “Autotune” calibration against manual calibration of building energy models". United States. https://doi.org/10.1016/j.apenergy.2016.08.073. https://www.osti.gov/servlets/purl/1311239.
@article{osti_1311239,
title = {Evaluation of “Autotune” calibration against manual calibration of building energy models},
author = {Chaudhary, Gaurav and New, Joshua and Sanyal, Jibonananda and Im, Piljae and O’Neill, Zheng and Garg, Vishal},
abstractNote = {Our paper demonstrates the application of Autotune, a methodology aimed at automatically producing calibrated building energy models using measured data, in two case studies. In the first case, a building model is de-tuned by deliberately injecting faults into more than 60 parameters. This model was then calibrated using Autotune and its accuracy with respect to the original model was evaluated in terms of the industry-standard normalized mean bias error and coefficient of variation of root mean squared error metrics set forth in ASHRAE Guideline 14. In addition to whole-building energy consumption, outputs including lighting, plug load profiles, HVAC energy consumption, zone temperatures, and other variables were analyzed. In the second case, Autotune calibration is compared directly to experts’ manual calibration of an emulated-occupancy, full-size residential building with comparable calibration results in much less time. Lastly, our paper concludes with a discussion of the key strengths and weaknesses of auto-calibration approaches.},
doi = {10.1016/j.apenergy.2016.08.073},
journal = {Applied Energy},
number = C,
volume = 182,
place = {United States},
year = {Fri Aug 26 00:00:00 EDT 2016},
month = {Fri Aug 26 00:00:00 EDT 2016}
}
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