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A statistical method for assessing retrofitting measures of buildings and ranking their robustness against climate change

Nik, Vahid LU ; Mata, Erika and Kalagasidis, Angela Sasic (2015) In Energy and Buildings 88. p.262-275
Abstract
Evaluating the usefulness and the reliability of retrofitted buildings for future climate can be a challenging task, while different scenarios and uncertainties exist both for retrofitting buildings and future climate. This paper presents a method to assess and quantify the relative robustness of retrofitting measures on long term, while climate variations in different time scales, extreme conditions and uncertainties of climate change are considered. The applicability of the method is examined by comparing two energy retrofitting measures for the existing residential building stock of Stockholm, whose energy performance is numerically simulated during 1961-2100 for five climate scenarios. The considered climate uncertainties are due to... (More)
Evaluating the usefulness and the reliability of retrofitted buildings for future climate can be a challenging task, while different scenarios and uncertainties exist both for retrofitting buildings and future climate. This paper presents a method to assess and quantify the relative robustness of retrofitting measures on long term, while climate variations in different time scales, extreme conditions and uncertainties of climate change are considered. The applicability of the method is examined by comparing two energy retrofitting measures for the existing residential building stock of Stockholm, whose energy performance is numerically simulated during 1961-2100 for five climate scenarios. The considered climate uncertainties are due to downscaling climate data from five different global climate models. The relative robustness of the retrofitting measures are evaluated in five time scales; hourly, daily, monthly, annual and 20-year period. The presented method facilitates the assessment and ranking of retrofitting measures, using few numbers. It also generates an overall view about the relative performance of retrofitting measures in different time scales. (C) 2014 Elsevier B.V. All rights reserved, (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Retrofitting buildings, Impact assessment, Climate change, Variations, Uncertainty, Statistical method, Robustness, Time scale
in
Energy and Buildings
volume
88
pages
262 - 275
publisher
Elsevier
external identifiers
  • wos:000349732100025
  • scopus:84920446161
ISSN
1872-6178
DOI
10.1016/j.enbuild.2014.11.015
language
English
LU publication?
yes
id
61569d06-bb8e-45da-8a0f-2d1323c182dd (old id 5305611)
date added to LUP
2015-04-23 17:08:00
date last changed
2017-11-19 03:24:31
@article{61569d06-bb8e-45da-8a0f-2d1323c182dd,
  abstract     = {Evaluating the usefulness and the reliability of retrofitted buildings for future climate can be a challenging task, while different scenarios and uncertainties exist both for retrofitting buildings and future climate. This paper presents a method to assess and quantify the relative robustness of retrofitting measures on long term, while climate variations in different time scales, extreme conditions and uncertainties of climate change are considered. The applicability of the method is examined by comparing two energy retrofitting measures for the existing residential building stock of Stockholm, whose energy performance is numerically simulated during 1961-2100 for five climate scenarios. The considered climate uncertainties are due to downscaling climate data from five different global climate models. The relative robustness of the retrofitting measures are evaluated in five time scales; hourly, daily, monthly, annual and 20-year period. The presented method facilitates the assessment and ranking of retrofitting measures, using few numbers. It also generates an overall view about the relative performance of retrofitting measures in different time scales. (C) 2014 Elsevier B.V. All rights reserved,},
  author       = {Nik, Vahid and Mata, Erika and Kalagasidis, Angela Sasic},
  issn         = {1872-6178},
  keyword      = {Retrofitting buildings,Impact assessment,Climate change,Variations,Uncertainty,Statistical method,Robustness,Time scale},
  language     = {eng},
  pages        = {262--275},
  publisher    = {Elsevier},
  series       = {Energy and Buildings},
  title        = {A statistical method for assessing retrofitting measures of buildings and ranking their robustness against climate change},
  url          = {http://dx.doi.org/10.1016/j.enbuild.2014.11.015},
  volume       = {88},
  year         = {2015},
}