A data-driven approach for quantifying energy savings in a smart building

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.