Commercial buildings show large discrepancies between estimated and actual energy consumption levels. Important challenges specifically lay in understanding the influence of human actions (by occupants and facility managers) on energy use and their contribution to commonly observed high energy consumption levels. This is particularly relevant in energy-intensive buildings such as laboratory facilities, which can typically consume up to five times more energy than other types of commercial buildings. This paper presents a framework to (1) collect relevant data about building energy performance and occupancy, (2) mine data, and (3) adapt and use energy analysis methods to understand the influence of occupants on energy performance, detect inefficiencies in the operation of building systems, and propose solutions. The framework is illustrated though a case study on a laboratory building in Madison, WI, identifying an excess of 40 percent in the energy consumption of the Heating, Ventilation and Air Conditioning System (HVAC).
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