UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

When activities connect: Sequencing, network analysis, and energy demand modelling in the United Kingdom

McKenna, E; Higginson, S; Hargreaves, T; Chilvers, J; Thomson, M; (2020) When activities connect: Sequencing, network analysis, and energy demand modelling in the United Kingdom. Energy Research and Social Science , 69 , Article 101572. 10.1016/j.erss.2020.101572. (In press).

[img] Text
When activities connect - accepted manuscript.pdf - Accepted version
Access restricted to UCL open access staff until 16 May 2021.

Download (489kB)

Abstract

This work applies a network analysis technique to the study of real and synthetic residential activity data commonly used in activity and energy demand research. UK Time Use Survey activity diaries are converted into network graphs of activity sequences. Differences between weekday and weekend networks are compared using network metrics: size, density, centrality and homophily. The results show that the weekday activity sequence network is smaller, less dense, more central and has lesser homophily than the weekend network. The technique is applied to test the validation of a model of residential active occupancy in buildings that uses a first-order Markov chain technique to generate synthetic data. The results show that the synthetic data reproduces relative differences between the network metrics for weekdays and weekends but the differences between real and synthetic data are statistically significant and greater or comparable to the differences observed between real weekday and weekend data. The first-order Markov chain technique fails to capture important characteristics of the sequence network that are present in the real data. The analysis technique presented here can be used to improve the testing and validation of such models in future, as well the comparative analysis of sets of aggregated activity data for periods of known difference in energy demand.

Type: Article
Title: When activities connect: Sequencing, network analysis, and energy demand modelling in the United Kingdom
DOI: 10.1016/j.erss.2020.101572
Publisher version: http://dx.doi.org/10.1016/j.erss.2020.101572
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Energy demand, Time use diary, Activity, Network theory, Network analysis, Markov chain, Bottom-up modelling
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
URI: https://discovery.ucl.ac.uk/id/eprint/10097657
Downloads since deposit
1Download
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item