Using Big Data to Tackle Building Energy Waste
Buildings cause $200 billion in energy waste each year. Business Insider reports on two enterprises that are using advanced technologies to fix inefficiencies within their buildings.
The General Services Administration (GSA) is using a proprietary algorithm developed by Massachusetts-based FirstFuel to save $13 million a year in energy costs across 180 buildings. After collecting basic electric meter data and address information from a client building, FirstFuel uses weather data, Geographic Information System (GIS) mapping, and a semantic public web search to gather detailed information on the client site. FirstFuel then uses the data generated by its algorithm to find areas of inefficiency.
For example, after analyzing the 4.1 million square foot Ronald Reagan building in Washington DC, FirstFuel found that two large exhaust fans were unnecessarily operating at full speed. Adjusting the fans’ setpoints to their original design levels contributed to the Reagan building saving $800,000 in one year.
Another enterprise using big data to drive energy savings is Kohl’s department stores. Kohl’s has installed energy-efficiency software in 1,200 stores nationwide, resulting in estimated energy cost savings between 8 percent and 18 percent.
Each Kohl’s site is monitored by a building automation system that is connected to the temperature control and lighting units. The data fed back to the building automation system shows if the fans are running, if the stages of heating or cooling are working and if lights are on or off.
Much of the energy waste in the retailer’s buildings stems from operational inefficiencies, like turning off lights and adjusting the air conditioning.
Photo via Shutterstock.
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