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Coupling a stochastic occupancy model to EnergyPlus to predict hourly thermal demand of a neighbourhood

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conference contribution
posted on 11.05.2016, 13:01 by Candy He, Timothy Lee, Simon Taylor, Steven Firth, Kevin Lomas
When designing and managing integrated renewable energy technologies at a community level, prediction of hourly thermal demand is essential. Dynamic thermal modelling, using deterministic occupancy profiles, has been widely used to predict the highresolution temporal thermal demand of individual buildings. Only in recent years has this approach started to be applied to simulate all buildings in a neighbourhood or an entire housing stock of a region. This study explores the potential of predicting hourly thermal demand for a group of dwellings by applying a stochastic occupancy model to dynamic thermal modelling. A case study with 125 new houses demonstrates the approach. The result was a more realistic and representative hourly thermal demand profile, compared to using standard deterministic occupancy profiles.

Funding

This work was funded under UK EPSRC grant EP/I002124/1 (Self Conserving Urban Environments – SECURE). SECURE is a consortium of four UK universities: Newcastle, Sheffield, Exeter and Loughborough. Website: https://www.secureproject. org/

History

School

  • Architecture, Building and Civil Engineering

Published in

14th Conference of International Building Performance Simulation Association (BS2015) http://www.ibpsa.org/?page_id=619

Pages

2101 - 2108 (8)

Citation

HE, M. ... et al, 2015. Coupling a stochastic occupancy model to EnergyPlus to predict hourly thermal demand of a neighbourhood. IN: Mathur, J. and Garg, V. (eds). Proceedings of the 14th International Conference of the International Building Performance Simulation Association (BS2015), 7th-9th December 2015, Hyderabad, India, pp. 2101 - 2108.

Publisher

© International Building Performance Simulation Association (IBPSA)

Version

VoR (Version of Record)

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/

Acceptance date

03/09/2015

Publication date

2015

Notes

This is a conference paper.

ISBN

9789352301188

Language

en

Location

Hyderabad, India

Exports

Loughborough Publications

Keywords

Exports