@article{36319,
  keywords = {Building Performance Simulation, SRG (Simulation Research Group), Building decarbonization, Occupant modeling, Climate resilience},
  author = {Amanda Fraga Krelling and Roberto Lamberts and Jeetika Malik and Wanni Zhang and Kaiyu Sun and Tianzhen Hong},
  title = {Defining weather scenarios for simulation-based assessment of thermal resilience of buildings under current and future climates: A case study in Brazil},
  abstract = {<p>In response to increasingly severe weather conditions, optimization of building performance and investment provides an opportunity to consider co-benefits of thermal resilience during energy efficiency retrofits. This work aims to assess thermal resilience of buildings using building performance simulation to evaluate the indoor overheating risk under nine weather scenarios, considering historical (2010s), mid-term future (2050s), and long-term future (2090s) typical meteorological years, and heat wave years. Such an analysis is based onresilience profiles that combine six integrated indicators. A case study with a district of 92 buildings in Brazil was&nbsp;conducted, and a combination of strategies to improve thermal resilience was identified. Results reflect the necessity of planning for resilience in the context of climate change. This is because strategies recommended<br />under current conditions might not be ideal in the future. Therefore, an adaptable design should be prioritized. Cooling energy consumption could increase by 48 % by the 2050s, while excessive overheating issues could reach 37 % of the buildings. Simple passive strategies can significantly reduce the heat stress. A comprehensive thermal resilience analysis should ultimately be accompanied by a thorough reflection on the stakeholder objectives, available resources, and planning horizon, as well as the risks assumed for not being resilient.&nbsp;</p>},
  year = {2024},
  journal = {Sustainable Cities and Society},
  volume = {107},
  pages = {105460},
  month = {07/2024},
  issn = {22106707},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S2210670724002877},
  doi = {10.1016/j.scs.2024.105460},
  language = {eng},
}