The Energy Policy Act of 2005 (EPACT 2005) required energy use in federal buildings to be metered. Since then, the US Army has installed electricity and natural gas meters on new and many existing facilities. To manage vast amounts of metered data from installations across the country, a centralized Metering Data Management System (MDMS) was put into place. MDMS continuously collects metered data, and makes it available at a central location for easy access. However, it quickly became clear that for the building energy data to be useful, it had to be put into context. CBECS and Energy Star’s portfolio manager provide context for commercial buildings in the private sector. A similar reference was needed for Army buildings that are often quite different in design and function to commercial buildings. The US Army Corps of Engineers (USACE) in collaboration with Pacific Northwest National Laboratory (PNNL) developed baseline models for five common Army building types. The focus of this initial study was on newly constructed buildings (post 2008) that were designed using standardized design documents created in response to EPACT 2005. Using metered data from these newly constructed buildings, EnergyPlus whole building energy models of the standard designs were calibrated. These models were then reverted to a Standard 90.1-2007 baseline using rules established by Appendix G of Standard 90.1-2007. The Standard 90.1-2007 baseline is important because it allows comparison of the performance of buildings to the EPACT 2005 requirement of building performance being 30% better than Standard 90.1-2007. This paper describes the methodology behind the creation of the baseline models and also describes how these models will be used to output results for MDMS. The methodology starts with processing of raw data from MDMS, choosing data for calibration, performing model calibration and reverting calibrated models to the Standard 90.1-2007 baseline. By using calibrated models to generate the baseline, the actual operating of buildings for a given location is captured in the models. The paper will describe the advantages and disadvantages of the approach, and will summarize ways in which baseline models will be used and how they will benefit MDMS and its users.
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