Abstract

Building energy models are largely comparative in nature, from early design phase to final energy code compliance models. While there is merit in a comparative framework, with the advent of empirical compliance targets, improving the efficacy of building energy models is imperative to better align model results with future building energy consumption. To refine this alignment, even early design phase energy models should undergo proper quality checking to improve the reliability of comparative studies and yield design strategy results that will hold true in later design phases and in future building energy consumption. Subject to time or user expertise, many early design phase energy models forgo proper quality checking, which can lead to misaligned expectations when the intent for a building owner is to ultimately meet empirical compliance targets. This paper outlines an automated approach to help energy modelers efficiently quality check early design phase energy models and minimize discrepancies between comparative modeling and empirically based performance targets. The test cases presented in this paper demonstrate how quality checking improves the reliability of early comparative studies.

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