A Data-driven Approach for Quantifying Energy Savings in a Smart Building

Authors: Rajendra Adhikari ; Xiangyu Zhang ; Manisa Pipattanasomporn ; Murat Kuzlu ; Saifur Rahman
Publisher: 2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
Published on: 10/30/2017
DOI: https://doi.org/10.1109/ISGT.2017.8085994
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Smart buildings with sensors, smart thermostats and energy consumption monitoring devices can collect a great amount of data, which can provide vital guidance for potential energy savings in buildings. Using a data-driven approach, this paper demonstrates that such data can be used to estimate energy saving potential of a building achievable through setpoint adjustments of a heating, ventilation and air conditioning (HVAC) system. A linear model is constructed to explain the relationship between the cooling set-point and the HVAC energy consumption. Data are collected for a building in Blacksburg, VA during the summer of 2016. Findings indicate that around 5 to 13% of energy savings can be achieved when the cooling set-point is increased by only one degree F.

Smart buildings , Building energy management , Energy efficiency , Big data