Peng, C. orcid.org/0000-0001-8199-0955 and Yi, C.Y. (2014) Climate change simulation for intelligent green building adaptation design. In: Proceedings of 2014 International Conference on Intelligent Green Building and Smart Grid, IGBSG 2014. 2014 International Conference on Intelligent Green Building and Smart Grid (IGBSG), 23-25 Apr 2014, Taipei. IEEE
Abstract
A climate change simulation framework for intelligent green building adaptation design is proposed. The simulation framework is developed for studying environmental performance of existing or proposed green buildings under present and future urban microclimate conditions. It draws on a synthesis of environmental computer simulation in three areas: (1) overall climate change scenario modelling at city level, (2) outdoor urban microclimate modelling at neighbourhood level, and (3) indoor environmental simulation at building level. A case study of applying the climate change simulation framework to an existing university campus green building is presented for 2012 and 2050. In response to the simulation results, strategies for adapting the case study green building in relation to its changing urban neighbourhood are assessed as an example. The case study shows that the simulation framework can generate requirements for intelligent green building adaptation design by linking urban microclimate change projection to simulated energy demand in maintaining building indoor thermal comfort. © 2014 IEEE.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 IEEE. This is an author produced version of a paper subsequently published in Proceedings of 2014 International Conference on Intelligent Green Building and Smart Grid, IGBSG 2014. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > School of Architecture (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 May 2016 10:33 |
Last Modified: | 19 Dec 2022 13:27 |
Published Version: | http://dx.doi.org/10.1109/IGBSG.2014.6835172 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/IGBSG.2014.6835172 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:79996 |