en
Scientific article
English

Deconstruct: A scalable method of as-built heat power loss coefficient inference for UK dwellings using smart meter data

Published inEnergy and Buildings, vol. 183, p. 443-453
Publication date2019
Abstract

Dwellings in the UK account for about 25% of global energy demand, of which 60% is space heating making this a key area for efficiency improvement. Dwelling UK Energy Performance Certificates (EPC) are currently based on surveyed data, rather than energy use monitoring. The installation of smart meters provides an opportunity to develop an EPC based on in situ dwelling thermal performance. This paper presents ‘Deconstruct' – a method of estimating the as-built Heat Power Loss Coefficient (HPLC) of occupied dwellings as a measure of thermal performance, using just smart-meter and meteorological data. Deconstruct is a steady-state grey box building model combined with a data processing pipeline and a model fitting method that limits the effects of confounding factors. Smart meter data from 780 UK dwellings from the UK Energy Demand Research Project (EDRP), was used to calculate a median HPLC of 0.28 kW/°C (±15%). The stability of the estimate across multiple years of data with different weather and energy use was demonstrated. Deconstruct was found to be suitable for large scale inference of dwelling thermal properties using the UK's new smart metering data infrastructure.

Keywords
  • Energy demand
  • Residential sector
  • Smart meter
  • Building assessment methods
  • Building energy models
Research group
Citation (ISO format)
CHAMBERS, Jonathan, ORESZCZYN, Tadj. Deconstruct: A scalable method of as-built heat power loss coefficient inference for UK dwellings using smart meter data. In: Energy and Buildings, 2019, vol. 183, p. 443–453. doi: 10.1016/j.enbuild.2018.11.016
Main files (1)
Article (Published version)
accessLevelRestricted
Identifiers
ISSN of the journal0378-7788
234views
0downloads

Technical informations

Creation01/14/2020 10:24:00 AM
First validation01/14/2020 10:24:00 AM
Update time03/15/2023 6:45:18 PM
Status update03/15/2023 6:45:17 PM
Last indexation05/05/2024 4:22:20 PM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack