Use of Energy and Other Monitored Data to Calibrate a Whole Building Energy Model

Abstract

This thesis documents an approach to utilize energy and other measured data to improve the calibration of a whole building energy model. Each chapter documents important steps of the process, and provides building energy analysts with insight on how to use this information to improve modeling assumptions, and hence energy model predictions. Important components of the study included creation of a custom, annual simulation weather file, designing and implementing an electrical sub-metering system, and disaggregating electrical energy use by model zone and energy end-use. Data and information were aggregated to create a DOE-2.2 whole building energy model, and the incremental improvement in model calibration was demonstrated as input assumptions were refined. The results of this study show accurate description of dynamic model inputs, particularly inputs that describe occupant's manipulation of building systems, was the most influential factor affecting energy model calibration.