Proposed method for probabilistic risk analysis using building performance simulations and stochastic parameters

• Main Authors: Ekström Tomas, Burke Stephen, Harderup Lars-Erik, Arfvidsson Jesper
• Format: Article
• Language: English
• Published: EDP Sciences 2020-01-01
• Series: E3S Web of Conferences
• Online Access: https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/32/e3sconf_nsb2020_25005.pdf

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.