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Journal article
Impact Assessment in the Process of Propagating Climate Change Uncertainties into Building Energy Use
Energies (Basel), v 14(2), p367
01 Jan 2021
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Buildings are subject to significant stresses due to climate change and design strategies for climate resilient buildings are rife with uncertainties which could make interpreting energy use distributions difficult and questionable. This study intends to enhance a robust and credible estimate of the uncertainties and interpretations of building energy performance under climate change. A four-step climate uncertainty propagation approach which propagates downscaled future weather file uncertainties into building energy use is examined. The four-step approach integrates dynamic building simulation, fitting a distribution to average annual weather variables, regression model (between average annual weather variables and energy use) and random sampling. The impact of fitting different distributions to the weather variable (such as Normal, Beta, Weibull, etc.) and regression models (Multiple Linear and Principal Component Regression) of the uncertainty propagation method on cooling and heating energy use distribution for a sample reference office building is evaluated. Results show selecting a full principal component regression model following a best-fit distribution for each principal component of the weather variables can reduce the variation of the output energy distribution compared to simulated data. The results offer a way of understanding compound building energy use distributions and parsing the uncertain nature of climate projections.
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Details
- Title
- Impact Assessment in the Process of Propagating Climate Change Uncertainties into Building Energy Use
- Creators
- Hamed Yassaghi - Drexel Univ, Dept Civil Architectural & Environm Engn, 3141 Chestnut St, Philadelphia, PA 19104 USASimi Hoque - Drexel University
- Publication Details
- Energies (Basel), v 14(2), p367
- Publisher
- Mdpi
- Number of pages
- 27
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:000611217600001
- Scopus ID
- 2-s2.0-85106222649
- Other Identifier
- 991019167694904721
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- Web of Science research areas
- Energy & Fuels