The IDEAL household energy dataset, electricity, gas, contextual sensor data and survey data for 255 UK homes

Martin Pullinger, Jonathan Kilgour* (Corresponding Author), Nigel Goddard, Niklas Berliner, Lynda Webb, Myroslava Dzikovska, Heather Lovell, Janek Mann, Charles Sutton, Janette Webb, Mingjun Zhong

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)
28 Downloads (Pure)

Abstract

AbstractThe IDEAL household energy dataset described here comprises electricity, gas and contextual data from 255 UK homes over a 23-month period ending in June 2018, with a mean participation duration of 286 days. Sensors gathered 1-second electricity data, pulse-level gas data, 12-second temperature, humidity and light data for each room, and 12-second temperature data from boiler pipes for central heating and hot water. 39 homes also included plug-level monitoring of selected electrical appliances, real-power measurement of mains electricity and key sub-circuits, and more detailed temperature monitoring of gas- and heat-using equipment, including radiators and taps. Survey data included occupant demographics, values, attitudes and self-reported energy awareness, household income, energy tariffs, and building, room and appliance characteristics. Linked secondary data comprises weather and level of urbanisation. The data is provided in comma-separated format with a custom-built API to facilitate usage, and has been cleaned and documented. The data has a wide range of applications, including investigating energy demand patterns and drivers, modelling building performance, and undertaking Non-Intrusive Load Monitoring research.
Original languageEnglish
Article number146
Number of pages18
JournalScientific Data
Volume8
Issue number1
Early online date28 May 2021
DOIs
Publication statusPublished - 28 May 2021

Bibliographical note

This paper is based on research funded by the UK Engineering and Physical Sciences Research Council and undertaking in the projects Intelligent Domestic Energy Advice Loop (grant reference EP/K002732/1) and Data-Driven Methods for a New National Household Energy Survey (grant reference EP/M008223/1). The authors are grateful to the research funding agency and to all those who participated directly in these projects alongside the authors: Prof. D.K. Arvind, Cillian Brewitt, Edmund Farrow, Elaine Farrow, Prof. Johanna Moore, Dr. Evan Morgan and Prof. David Shipworth. Thanks also to the participants in the project, whose participation made this dataset and other work in the projects possible, and to Changeworks (https://www.changeworks.org.uk/) for identifying and recruiting potential participants, managing participant interactions, and installing and maintaining homes’ sensor and app systems

Keywords

  • Statistics, Probability and Uncertainty
  • Statistics and Probability
  • Education
  • Library and Information Sciences
  • Information Systems
  • Computer Science Applications

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