@inproceedings{01HDGHD4Q5NE091DQB7QKX977R,
  abstract     = {{In Belgium 64% of the apartment blocks date from before 1982. These buildings generally do not meet contemporary energy and comfort standards. At the same time, apartment buildings have become of growing importance in the Belgian building stock in recent decades. Consequently, these old apartment buildings offer an enormous potential for thorough renovation in order to meet today’s housing needs and to further improve the energy performance of the existing housing stock. Ample studies have shown that the actual energy use of a dwelling largely depend on the behaviour and habits of its inhabitants. In order to evaluate the current energy performance requirements, it is important to consider a wide range of user profiles. However, it is likely that in a multifamily building there is diverse mix of these profiles, so that the spread of energy use is somewhat averaged out. To estimate the energy use in an apartment block, a multizone thermal building simulation model will be build, validated by measurement data of a case study building. By defining certain input parameters as random variables following a predefined probability distribution and running the energy simulation numerous times, a range of outputs can be generated using the Monte Carlo method. Since every apartment is characterized by a different energy demand and thus interacts differently with the collective heating system, every unit would ideally be modelled as an individual energy zone. But for a multifamily building with 50 units or more, the computation time would increase enormously, which hinders the Monte Carlo approach. In this paper, a methodology to tackle this issue is developed and discussed. This will enable to estimate the distribution of the energy use of an apartment block for a wide variety of energy-saving measures and building geometries.}},
  author       = {{Van de Putte, Stijn and Steeman, Marijke and Janssens, Arnold}},
  booktitle    = {{2nd International Conference on Construction, Energy, Environment & Sustainability (CEES 2023), Proceedings}},
  isbn         = {{9789895449934}},
  language     = {{eng}},
  location     = {{Funchal, Portugal}},
  pages        = {{8}},
  publisher    = {{Itecons - Instituto de Investigação e Desenvolvimento Tecnológico para a Construção, Energia, Ambiente e Sustentabilidade}},
  title        = {{Methodology for dynamic simulations of energy use in multifamily buildings}},
  url          = {{https://www.cees2023.uc.pt/projectos/cees2023/index.php?module=sec&id=954&f=1}},
  year         = {{2023}},
}