A high-temporal resolution residential building occupancy model to generate high-temporal resolution heating load profiles of occupancy-integrated archetypes

Files in This Item:
File Description SizeFormat 
Buttitta J2.pdf2.43 MBAdobe PDFDownload
Title: A high-temporal resolution residential building occupancy model to generate high-temporal resolution heating load profiles of occupancy-integrated archetypes
Authors: Buttitta, GiuseppinaFinn, Donal
Permanent link: http://hdl.handle.net/10197/11566
Date: 1-Jan-2020
Online since: 2020-09-15T13:24:34Z
Abstract: A strong correlation exists between occupant behaviour and space heating energy use. In particular, the occupancy status (e.g., daytime absence) is known to have a significant influence on residential heating load profiles, as well as on cumulative heating energy consumption. In the literature, many occupancy models have been utilised to predict occupancy profiles of individual dwellings as part of the larger residential building stock. However, none of the existing models consider diversity associated with occupancy-integrated archetypes to generate high-temporal resolution heating load profiles. The current paper uses Time Use Survey (TUS) data to develop a high-temporal resolution residential building occupancy model. The key feature of the proposed model, implemented using MATLAB, is the ability to generate stochastic occupancy time-series data for national population subgroups characterised by specific occupancy profiles. It is shown that the results are capable of closely approximating data available from TUS. The developed model can be applied to improve the quality of modelled high-temporal resolution heating load profiles for generic building stock characterised by population subgroups represented by different occupancy-integrated archetypes. A case study is performed on a building stock sample located in London, UK. The developed occupancy model has been implemented in MATLAB and is available for download.
Funding Details: European Commission Horizon 2020
University College Dublin
Type of material: Journal Article
Publisher: Elsevier
Journal: Energy and Buildings
Volume: 206
Copyright (published version): 2019 Elsevier
Keywords: Stochastic occupancy modelsArchetypesBuilding stock modellingResidential buildingsOccupancy profiles
DOI: 10.1016/j.enbuild.2019.109577
Language: en
Status of Item: Peer reviewed
Appears in Collections:Mechanical & Materials Engineering Research Collection

Show full item record

Page view(s)

96
checked on Sep 22, 2020

Download(s)

8
checked on Sep 22, 2020

Google ScholarTM

Check

Altmetric


This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.