Energy Use Insights from Inverse Thermodyanmic-Based Modeling of Residential Buildings

This presentation investigates the use of utility billing data for residential buildings, combined with highly granular weather data to disaggregate energy data into end uses, determine the type of HVAC system in use, and predict future months’ disaggregated energy use. This is accomplished through the use of an inverse thermodynamic-based model that uses binned temperature values.  This methodology was verified using a dataset of several hundred homes. The resulting information can provide insights to residential building customers to motivate energy savings behaviors.