besos: Building and energy simulation, optimization and surrogate modelling
Date
2021
Authors
Westermann, Paul
Christiaane, Theodor Victor
Beckett, Will
Kovacs, Paul
Evins, Ralph
Journal Title
Journal ISSN
Volume Title
Publisher
Journal of Open Source Software
Abstract
The 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.
Description
Keywords
Energy in Cities, Institute for Integrated Energy Systems (IESVic)
Citation
Westermann, 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.02677