The importance of improving the energy efficiency of buildings has been recognised as critical to decrease greenhouse gas emissions from building energy production to meet the UK government’s target on net-zero emissions. While the official documentation for building energy performance, the Energy Performance Certificates (EPCs), have been commonly considered as inaccurate, a detailed understanding of the energy performance of the existing building stock is still much needed.

This PhD aims at developing a hybrid grey-box framework for residential building thermal consumption estimation based on properties’ geometric and thermal characteristics. Three Work Packages are designed to progressively investigate how different data and methodologies can be utilised to achieve the best prediction performance with minimum manual-interpreted data input.

PhD Candidate: Yulan Sheng

Supervisory Team: Martin Mayfield-Tulip, Mauricio Álvarez

Project Status: Ongoing

Project Start Date: 1st March 2020

Keywords: Housing, Energy, EPC, 3D reconstruction, Thermography, Machine Learning

Funding Scheme: Energy Institute Scholarship