Building-level occupancy data to improve ARIMA-based electricity use forecasts

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Conference2nd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings (BuildSys 2010): 02 November 2010, Zurich, Switzerland
Pages1318; # of pages: 6
AbstractThe energy use of an office building is likely to correlate with the number of occupants, and thus knowing occupancy levels should improve energy use forecasts. To gather data related to total building occupancy, wireless sensors were installed in a three-storey building in eastern Ontario, Canada comprising laboratories and 81 individual work spaces. Contact closure sensors were placed on various doors, PIR motion sensors were placed in the main corridor on each floor, and a carbon-dioxide sensor was positioned in a circulation area. In addition, we collected data on the number of people who had logged in to the network on each day, network activity, electrical energy use (total building, and chilling plant only), and outdoor temperature. We developed an ARIMAX model to forecast the power demand of the building in which a measure of building occupancy was a significant independent variable and increased the model accuracy. The results are promising, and suggest that further work on a larger and more typical office building would be beneficial. If building operators have a tool that can accurately forecast the energy use of their building several hours ahead they can better respond to utility price signals, and play a fuller role in the coming Smart Grid.
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AffiliationNRC Institute for Research in Construction; National Research Council Canada
Peer reviewedYes
NRC number53566
NPARC number20373899
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Record identifier65c7fdd7-c971-41e1-ba65-0fa3ff650f75
Record created2012-07-23
Record modified2016-05-09
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