Paper Conference

Proceedings of eSim 2020: 11th Conference of IBPSA-Canada

     

A calibrated RC model for data-driven retrofit analysis of a residential building

Diego Sigrist, Chirag Deb, Arno Schlueter
ETH Zurich, Switzerland

Abstract: Among other reasons, the low building retrofit rate in Switzerland is attributed to modeling barriers: a lack of accurate assessment of building energy performance in the pre-retrofit phase as well as the difficulty to model the energy performance in the post-retrofit phase. We propose a novel resistor-capacitor (RC) model that is calibrated with geometric and physical building information (area specifications and Uvalues) as well as hourly in-situ measurement data over three weeks. The calibrated RC model is able to accurately simulate not only the thermal behavior of the current building state but also the energy savings for different retrofit strategies, and can thus serve as a data-driven decision-tool in the building retrofit process.
Paper:
esim2020_1184