Proposed Method for Probabilistic Risk Analysis using Building Performance Simulations and Stochastic Parameters
(2020) 12th Nordic Symposium on Building Physics In E3S Web of Conferences 172.- Abstract
- As parts of the world continue the work of mitigating the impact of climate change, many countries strive for continued reductions in energy demand from buildings by implementing more stringent building regulations. Consequently, the importance of accurate and efficient building performance simulations to predict the energy use of a building design increases. As observed in earlier studies, there are performance gaps between the predicted annual energy demand from building energy performance simulations based on deterministic methods compared to the monitored annual energy use of a building. This paper presents a preliminary method developed using probabilistic methods for risk analysis and building performance simulations to predict the... (More)
- As parts of the world continue the work of mitigating the impact of climate change, many countries strive for continued reductions in energy demand from buildings by implementing more stringent building regulations. Consequently, the importance of accurate and efficient building performance simulations to predict the energy use of a building design increases. As observed in earlier studies, there are performance gaps between the predicted annual energy demand from building energy performance simulations based on deterministic methods compared to the monitored annual energy use of a building. This paper presents a preliminary method developed using probabilistic methods for risk analysis and building performance simulations to predict the energy performance of buildings using stochastic parameters. The method is used to calculate the probability for the energy performance of a building design to fulfil the energy requirements. The consequences are quantified using an example of energy performance contracting to evaluate the inherent risk of a building’s design. The method was demonstrated in a case study and validated by comparing the results in energy performance and probability of failure against measured data from 26 single-family houses. (Less)
- Abstract (Swedish)
- As parts of the world continue the work of mitigating the impact of climate change, many countries strive for continued reductions in energy demand from buildings by implementing more stringent building regulations. Consequently, the importance of accurate and efficient building performance simulations to predict the energy use of a building design increases. As observed in earlier studies, there is a performance gap between the predicted annual energy demand from building energy performance simulations based on deterministic methods compared to the monitored annual energy use of a building. This paper presents a preliminary method developed for probabilistic risk analysis of the energy performance of buildings using stochastic parameters.... (More)
- As parts of the world continue the work of mitigating the impact of climate change, many countries strive for continued reductions in energy demand from buildings by implementing more stringent building regulations. Consequently, the importance of accurate and efficient building performance simulations to predict the energy use of a building design increases. As observed in earlier studies, there is a performance gap between the predicted annual energy demand from building energy performance simulations based on deterministic methods compared to the monitored annual energy use of a building. This paper presents a preliminary method developed for probabilistic risk analysis of the energy performance of buildings using stochastic parameters. The method is used to calculate the probability for the energy performance of a building design to fulfil the energy requirements. Then the consequences are quantified and used to evaluate the inherent risk of a building design. The method was evaluated in a case study – applied to 26 single-family homes - and tested against measured data. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/f9021c15-b4cf-4441-ada0-2534acc11a42
- author
- Ekström, Tomas LU ; Burke, Stephen LU ; Harderup, Lars-Erik LU and Arfvidsson, Jesper LU
- organization
- publishing date
- 2020
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 12th Nordic Symposium on Building Physics (NSB 2020)
- series title
- E3S Web of Conferences
- volume
- 172
- article number
- 25005
- conference name
- 12th Nordic Symposium on Building Physics
- conference location
- Tallinn, Estonia
- conference dates
- 2020-06-14 - 2020-06-17
- external identifiers
-
- scopus:85088462518
- DOI
- 10.1051/e3sconf/202017225005
- project
- Predicting the Energy Performance of Buildings - A Method using Probabilistic Risk Analysis for Data-driven Decision-support
- language
- English
- LU publication?
- yes
- id
- f9021c15-b4cf-4441-ada0-2534acc11a42
- date added to LUP
- 2020-01-27 13:44:22
- date last changed
- 2022-04-18 23:57:21
@inproceedings{f9021c15-b4cf-4441-ada0-2534acc11a42,
abstract = {{As parts of the world continue the work of mitigating the impact of climate change, many countries strive for continued reductions in energy demand from buildings by implementing more stringent building regulations. Consequently, the importance of accurate and efficient building performance simulations to predict the energy use of a building design increases. As observed in earlier studies, there are performance gaps between the predicted annual energy demand from building energy performance simulations based on deterministic methods compared to the monitored annual energy use of a building. This paper presents a preliminary method developed using probabilistic methods for risk analysis and building performance simulations to predict the energy performance of buildings using stochastic parameters. The method is used to calculate the probability for the energy performance of a building design to fulfil the energy requirements. The consequences are quantified using an example of energy performance contracting to evaluate the inherent risk of a building’s design. The method was demonstrated in a case study and validated by comparing the results in energy performance and probability of failure against measured data from 26 single-family houses.}},
author = {{Ekström, Tomas and Burke, Stephen and Harderup, Lars-Erik and Arfvidsson, Jesper}},
booktitle = {{12th Nordic Symposium on Building Physics (NSB 2020)}},
language = {{eng}},
series = {{E3S Web of Conferences}},
title = {{Proposed Method for Probabilistic Risk Analysis using Building Performance Simulations and Stochastic Parameters}},
url = {{http://dx.doi.org/10.1051/e3sconf/202017225005}},
doi = {{10.1051/e3sconf/202017225005}},
volume = {{172}},
year = {{2020}},
}