besos: Building and Energy Simulation, Optimization and Surrogate Modelling

Abstract

License Authors of papers retain copyright and release the work under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Summary The buildings sector is one of the largest contributors to CO 2 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. Figure 1: analysis domains encompassed by BESOS.