As efficiency gains are made in building lighting and HVAC systems, plug loads become a greater percentage of building energy use and must be addressed to meet energy goals. HVAC and lighting systems are targeted because they are typically the highest energy end uses, but plug load reduction and control should be considered as part of a comprehensive approach to energy reduction.
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Empirical techniques for characterizing electrical energy use now play a key role in reducing electricity consumption, particularly miscellaneous electrical loads, in buildings. Identifying device operating modes (mode extraction) creates a better understanding of both device and system behaviors. Using clustering to extract operating modes from electrical load data can provide valuable insights into device behavior and identify opportunities for energy savings. We present a fast and effective heuristic clustering method to identify and extract operating modes in electrical load data.
This paper documents the methodology developed to identify and reduce plug and process loads (PPLs) as part of NREL's Research Support Facility's (RSF) low energy design process. PPLs, including elevators, kitchen equipment in breakrooms, and office equipment in NREL’s previously occupied office spaces were examined to determine a baseline. This, along with research into the most energy-efficient products and practices, enabled the formulation of a reduction strategy that should yield a 47% reduction in PPLs. The building owner and the design team played equally important roles in developing and implementing opportunities to reduce PPLs. Based on the work done in the RSF, a generalized multistep process has been developed for application to other buildings.