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A cross analysis of existing methods for modelling household appliance use

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journal contribution
posted on 08.08.2018, 10:03 authored by Y. Yamaguchi, Selin Yilmaz, N. Prakash, Steven FirthSteven Firth, Y. Shimoda
This paper presents a cross-analysis of the existing methods for modelling the use of household appliances and aims to provide insights into modelling approaches for researchers and designers. Five factors regarding appliance use modelling that have a significant impact on the modelling performance are defined: consideration of the intra/inter-household variation, consideration of the influence of socio-demographic conditions, time resolution of the data, quantification of model calibration parameters and applicability to a variety of modelling contexts. Four existing modelling methods commonly used in literature for modelling appliance use are studied to address these factors. Monitored data of 333 multi-family buildings in Japan and a Japanese time use survey are used in the cross-analysis to simulate the switch-on time profiles for the case of washing machines. The design of future research studies (including monitoring strategies, modelling and sample sizes) are discussed to further improve the ability to model home appliance use.

Funding

This work was supported by JST CREST under [Grant JPMJCR15K4], Japan, and Engineering and Physical Sciences Research Council under [Grant EP/H009612/1], UK.

History

School

  • Architecture, Building and Civil Engineering

Published in

Journal of Building Performance Simulation

Citation

YAMAGUCHI, Y. ... et al, 2018. A cross analysis of existing methods for modelling household appliance use. Journal of Building Performance Simulation, 12 (2), pp.160-179.

Publisher

Taylor & Francis © International Building Performance Simulation Association (IBPSA)

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2018

Notes

This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Building Performance Simulation on 21 July 2018, available online: http://www.tandfonline.com/10.1080/19401493.2018.1497087.

ISSN

1940-1493

eISSN

1940-1507

Language

en