With the support of EN-TRACK, this interesting research has been published in Energies. It assesses how interpretable and scalable data-driven methodologies are able to provide predictions for energy use in buildings. This is essential for the accurate measurement and verification of energy renovation projects and has the potential of unlocking considerable investments in energy efficiency worldwide.
This paper proposes a Bayesian linear regression methodology that enables a detailed characterization of the analyzed buildings through the detection of typical electricity usage profiles and the estimation of the weather dependence. The range of additional results and insights provided by Bayesian methodologies prove very interesting for Measurement & Verification applications and open possibilities for de-risking analyses in energy efficiency projects.
Read the full article here.