Many buildings are now collecting a large amount of data on operations, energy consumption and activities through systems such as building management system (BMS), sensors and meters (sub-meters, smart meters). However, the majority of data are not utilized and thrown away. Science and mathematics can play an important role in utilizing these big data and helping us accurately assess how we consume energy in buildings and what we can do to save energy, make buildings energy efficient and reduce GHG emissions. We developed an analytical tool which can assist building owners, facility managers, operators and tenants of buildings in assessing, benchmarking, diagnosing, tracking, forecasting, simulating and optimizing energy consumption in building portfolios.
By: Young M. Lee, Lianjun An, Fei Liu, Raya Horesh, Young Tae Chae, Rui Zhang
Published in: Annals of the New York Academy of Sciences - Implications of a Data Driven-Built Environment,, vol.1295, p.18-25 (10.1111/nyas.12193) ) in 2013
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