Westermann, PaulChristiaane, Theodor VictorBeckett, WillKovacs, PaulEvins, Ralph2025-09-092025-09-092021Westermann, P. Christiaansem T.V. Beckett, W. Kovacs, P. Evins, R. (2021) besos: Building and energy simulation, optimization and surrogate modelling. The Journal of Open Source Software, 60, 2677. https://doi.org/10.21105/joss.02677https://doi.org/10.21105/joss.02677https://hdl.handle.net/1828/22739The buildings sector is one of the largest contributors to CO2 emissions, comprising up to 33% of the global total (ürge-Vorsatz et al., 2007). Improved computational methods are needed to help design more energy-efficient buildings. The Python library besos along with its associated web-based platform BESOS help researchers and practitioners explore energy use in buildings more effectively. This is achieved by providing an easy way of integrating many disparate aspects of building modelling, district modelling, optimization and machine learning into one common library.enAttribution 4.0 InternationalEnergy in CitiesInstitute for Integrated Energy Systems (IESVic)besos: Building and energy simulation, optimization and surrogate modellingArticleDepartment of Civil Engineering