Uncertainty in the energy dynamics of commercial office buildings

Abstract

Whole-building energy models take information about the structure of a building, its equipment (electrical loads, lights, conditioning equipment, etc.), and disturbances (people, weather) and predict its year long comfort and energy performance. Both commercial and freely available tools are available for performing these time-domain simulations, which are used for design trade studies and more frequently to check for energy consumption and comfort compliance. These models require hundreds of assumptions as input when it comes to parameterizing the building model. Previous studies have investigated how predictions are influenced by these assumptions and which of the parameters are critical to year-long calculations. In this paper we extend this approach to investigate how parametric uncertainty influences uncertainty in the energy dynamics within a building. We provide a case study that investigates an office building by extracting dynamic information out of an EnergyPlus model, and supplies this information to an automatically generated analytical thermal network model. We conclude with a control-oriented frequency-based robustness assessment as well as a study of how uncertainty influences the network structure of the building by investigating the spectral gap of its graph Laplacian.