by David Keith of
Marshall Design, Inc.
The use of occupancy sensors as lighting controls in individual offices provides a great opportunity for reducing energy use and peak demand.
The results of on-going research into office occupancy patterns show that, for the facility investigated, individual offices are typically occupied only 50% of the workweek, defined as between 8 am and 5 pm from Monday through Friday. When considering only the portion of each day between the first visit to the office and the last, the office occupancy rate is 60%, for Monday through Friday from 8 am through 6 pm. This indicates a potential energy reduction of 40% for using occupancy sensors to control the lighting in individual offices.
In addition, for groups of offices, the reduction of peak demand is significant. For groups of at least 50 offices, the potential reduction in demand charges is 25% on average. For smaller groups, the potential savings are lower, with 10% reduction expected on average. The likelihood of achieving substantial demand reduction increases as the number of offices included is increased.
The studies referenced were made at the National Center for Atmospheric Research (NCAR) Foothills Laboratory in Boulder, CO which is an independent scientific and research facility. The offices were randomly selected across the entire facility, so they include both scientist and office staff offices. Each individual office was monitored for an entire year, so the results do reflect long term and persistent patterns of occupancy.
Research by others has shown different occupancy rates, and that different facilities have different occupancy patterns. Comparison of the results from the NCAR facility with a shorter term study of a university facility in Wisconsin showed that the results were similar, but the potential savings for peak demand were less. This is probably the effect of the more coordinated schedule which exists at a university, where many instructors will be in and out of offices according to the class schedule, which is the same across the entire facility. By comparison the NCAR facility will have a more random pattern, and this should correspond to a greater reduction in peak demand.
The NCAR facility data does include a typical occupancy sensor time delay, which was adjusted by occupants. Increasing the time delays will of course reduce energy savings and demand reduction. Finally, the overall economic effect will depend significantly on the luminaires, and particularly the fluorescent ballasts, being controlled.
For additional information, I recommend looking at the research by the Lawrence Berkeley National Laboratory (LBNL), and the publications of the Electric Power Research Institute (EPRI) and the Lighting Research Center (LRC).
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