Investigating the importance of future climate typology on estimating the energy performance of buildings in the EPFL campus
(2017) CISBAT 2017 International ConferenceFuture Buildings & Districts In Energy Procedia 122. p.1087-1092- Abstract
- Climate changes induce warmer climate with stronger and more frequent extreme events. Due to the uncertain nature of climate, accurate simulation of future conditions is impossible and a major challenge is the selection of climate data in the impact assessment. This work compares application of three climate data sets in an energy simulation of the EPFL campus: i) Regional Climate Models (RCM data), ii) statically representative RCM data, and iii) morphed data. The energy behavior of the campus is analyzed, including its future thermal behavior, as well as its dynamic hourly variation due to the climatic data. The objective of this paper is to understand and quantify the energy transition, from 2010 to 2100, by focusing on the thermal... (More)
- Climate changes induce warmer climate with stronger and more frequent extreme events. Due to the uncertain nature of climate, accurate simulation of future conditions is impossible and a major challenge is the selection of climate data in the impact assessment. This work compares application of three climate data sets in an energy simulation of the EPFL campus: i) Regional Climate Models (RCM data), ii) statically representative RCM data, and iii) morphed data. The energy behavior of the campus is analyzed, including its future thermal behavior, as well as its dynamic hourly variation due to the climatic data. The objective of this paper is to understand and quantify the energy transition, from 2010 to 2100, by focusing on the thermal behavior of buildings, as well as their energy demand for heating and cooling. Results explain the difference between three cases, underling the important impact related to a sound selection of the weather data. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7492569e-a82c-4d87-a33f-d79f10532e1a
- author
- Nik, Vahid
LU
; Coccolo, Silvia ; Kämpf, Jérôme and Scartezzini, Jean-Louis
- organization
- publishing date
- 2017-09
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- climate change, energy simulation, climate uncertainty, weather data, extreme conditions
- in
- Energy Procedia
- volume
- 122
- pages
- 1087 - 1092
- publisher
- Elsevier
- conference name
- CISBAT 2017 International ConferenceFuture Buildings & Districts
- conference location
- Lausanne, Switzerland
- conference dates
- 2017-09-06 - 2017-09-08
- external identifiers
-
- scopus:85029895199
- wos:000411783600182
- ISSN
- 1876-6102
- DOI
- 10.1016/j.egypro.2017.07.434
- language
- English
- LU publication?
- yes
- id
- 7492569e-a82c-4d87-a33f-d79f10532e1a
- date added to LUP
- 2017-10-01 17:13:52
- date last changed
- 2022-02-16 01:12:54
@article{7492569e-a82c-4d87-a33f-d79f10532e1a, abstract = {{Climate changes induce warmer climate with stronger and more frequent extreme events. Due to the uncertain nature of climate, accurate simulation of future conditions is impossible and a major challenge is the selection of climate data in the impact assessment. This work compares application of three climate data sets in an energy simulation of the EPFL campus: i) Regional Climate Models (RCM data), ii) statically representative RCM data, and iii) morphed data. The energy behavior of the campus is analyzed, including its future thermal behavior, as well as its dynamic hourly variation due to the climatic data. The objective of this paper is to understand and quantify the energy transition, from 2010 to 2100, by focusing on the thermal behavior of buildings, as well as their energy demand for heating and cooling. Results explain the difference between three cases, underling the important impact related to a sound selection of the weather data.}}, author = {{Nik, Vahid and Coccolo, Silvia and Kämpf, Jérôme and Scartezzini, Jean-Louis}}, issn = {{1876-6102}}, keywords = {{climate change; energy simulation; climate uncertainty; weather data; extreme conditions}}, language = {{eng}}, pages = {{1087--1092}}, publisher = {{Elsevier}}, series = {{Energy Procedia}}, title = {{Investigating the importance of future climate typology on estimating the energy performance of buildings in the EPFL campus}}, url = {{http://dx.doi.org/10.1016/j.egypro.2017.07.434}}, doi = {{10.1016/j.egypro.2017.07.434}}, volume = {{122}}, year = {{2017}}, }