Carnegie Mellon University

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An EnergyPlus whole building energy model calibration method for office buildings using occupant behavior data mining and empirical data

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journal contribution
posted on 2014-01-01, 00:00 authored by Khee Poh Lam, Jie Zhao, B. Erik Ydstie, Jason Wirick, Meiwei Qi, Jihyun Park
This paper proposes a method comprising procedures to calibrate an EnergyPlus whole building energy model. An occupant behavior data mining procedure is developed and tested in an office building. Workday occupancy schedules are generated by mining the office appliance energy consumption data. Hourly and monthly power, energy, and temperature data are collected and used for lighting, equipment and HVAC systems energy performance calibration. The result shows a 1.27% mean bias error for the total annual energy use intensity. The proposed calibration method provides a scientific and systematic framework to conduct high accuracy EnergyPlus model calibration.




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