Building performance optimisation tools for the decarbonisation of Swedish buildings

Abstract: To mitigate climate change and reach Sweden’s goal of becoming carbon neutral by 2045, or at an earlier stage of 2030 for 23 Swedish cities, urgent action is required to reduce greenhouse gas emissions. Due to the building sector’s significant contribution to carbon emissions, a crucial aspect in achieving these goals is improving the energy efficiency of existing buildings, as most of these will still be in use by this time. To improve the energy performance of these buildings, various renovation measures can be applied, where the choice of the best strategies involves being confronted with multiple conflicting objectives such as reducing energy demand, minimising environmental impact, and managing costs, which can be assessed using advanced building performance simulation tools. Finding the most appropriate renovation solutions involves testing a significant number of different combinations, which can become a very time-consuming process; therefore, optimising the simulation process is essential, especially in large-scale renovations. This study investigates the effect of using different existing building performance optimisation tools to accelerate the process of finding the most optimal renovation packages for Swedish buildings, with a focus on achieving decarbonisation in a cost-effective manner. A parametric model was created in Grasshopper to analyse three different optimisation tools, including Octopus, Wallacei and Opossum. Their performance was compared to Colibri components, which were used to carry out a ‘brute force’ to obtain results for energy use intensity, global warming potential and cost, for all possible renovation packages. The evaluation process was conducted in three main parts. The first involved testing 1260 combinations of different passive renovation measures on a simple shoebox model; the second considered both the same model and passive renovation measures, in addition to a number of active renovation measures, resulting in a total of 10 080 combinations to assess the optimisation tools’ performance when considering a larger number of iterations; and the third consisted of testing only the passive measures on a more complex geometry, modelled after a real building. The utilisation of optimisation tools proved to be very effective in accelerating the simulation and assessment process, while maintaining satisfactory precision in achieving optimal results, enhancing the applicability of parametric design as well as its practicality. Opossum was found to be the most efficient tool and reduced the total simulation time by 90 %, while upholding an acceptable level of accuracy in achieving optimal solutions. Additionally, Wallacei proved to be a feasible choice, as it provides the user with a number of useful postprocessing features. For the real building model, the most optimal packages generally consisted of glass wool or cellulose fibre insulation at varying thicknesses, for both the walls and roof as well as the installation of a storm window. Although active measures were not applied to the real building model, the installation of a PV system was required for reaching carbon neutrality, as this was the only climate compensation considered in this study.