New study of buildings suggests additional approaches to energy efficiency

By By Peter Dizikes, MIT News Office | 30 Mar 2012

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Many workplaces feature major changes in occupancy. In academic buildings, hundreds of students may pour in for a lecture, then leave an hour or two later, while faculty, researchers and staff can enter and exit in irregular patterns. In commercial structures, workers may come and go en masse during short time periods during the day. As a result, energy use in virtually all workspaces can rapidly become inefficient - too large or too small - in relation to the number of people inside.

Now, a new study done on MIT buildings reveals some data that could help designers and building managers, on campuses or in the commercial sector, optimise energy usage - and suggests a template for conducting more research on the subject.

The study, published in the April issue of the journal Energy and Buildings, examines data from MIT's buildings M37 and E52, and finds that while electricity use corresponds to occupancy fairly well in those spaces, the activity of heating, ventilation and air conditioning (HVAC) systems in the buildings does not correlate closely to occupancy.

"It can take a huge amount of energy to heat up buildings during the day, and then suddenly there may be nobody there," says co-author Carlo Ratti, director of the Senseable City Laboratory and associate professor of the practice in MIT's department of urban studies and planning (DUSP). "There is significant potential for improvement and savings, if you could get a more dynamic usage of energy in this area."

As Ratti and the co-authors note, the federal government estimates that commercial buildings account for about 20 per cent of US energy consumption, and 12 per cent of US contributions to greenhouse gas emissions; past studies have shown that commercial buildings could reduce their energy use 20 to 30 per cent by implementing strategies that better match energy use and need. 

The new study uses data about Wi-Fi connections as a proxy for building occupancy, a method the researchers believe could be replicated elsewhere at low cost; while the data does not necessarily reveal an exact population count inside buildings, it does indicate relative occupancy levels over time. "It's a way of trying to make use of information that already exists," Ratti says.

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