New Publication in Data-Centric Engineering Journal on Heat Pump Performance Estimation
12/14/2024Our new study presents a novel method for predicting the average performance of heat pumps across all buildings in a city using an unpaired dataset of heat pump electricity and gas smart meter data. This research enables a fully data-driven evaluation of heat pump performance.
This paper proposes a novel method for estimating the seasonal performance factor (SPF) of heat pumps using an unpaired dataset of smart meter data. The knowledge of the actual SPF is especially important for simulation new, retrofitted heat pumps.
By comparing the distributions of annual gas and heat pump electricity consumption with statistical tests, the methodology predicts the SPF and thereupon the electricity consumption of future heat pumps replacing gas furnaces. The approach was evaluated and validated on a real-world dataset.
You can read the full version (open access) on the journal website.
The two authors of this publication are Daniel Bayer and Marco Pruckner.
