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.

Popular Abstract

This study showed that the investigated optimisation tools were able to significantly reduce the time taken for analysing different renovation options that would lower the environmental impact of Swedish buildings. The utilisation of these tools allowed the identification of the most effective renovation strategies that could minimise the energy use of the building, its environmental impact, and the associated costs, with a time reduction of around 90 %. In practice, testing design ideas can become extremely time consuming; therefore, optimisation tools can aid consultants in combating this issue, while allowing for a larger focus on other areas.

Sweden has a goal of becoming carbon neutral by 2045, or at an earlier stage of 2030 for 23 Swedish cities. The building sector contributes to a significant portion of carbon emissions; thus, reducing the impact of buildings is a crucial aspect in achieving these goals. An important part of this is improving the energy efficiency of existing buildings, as most of these will still be in use by this time. When renovating a building, 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 and decision-making process is essential, especially in the large-scale renovations that are required for bringing us closer to achieving climate neutrality goals.

In this study, the effect of using different existing building performance optimisation tools was investigated, aiming to accelerate the process of finding the most optimal renovation strategies for Swedish buildings, with a focus on achieving decarbonisation in a cost-effective manner. A parametric model was created in the software ‘Grasshopper’ to analyse three different optimisation tools, including Octopus, Wallacei and Opossum. Their performance was compared to another tool called Colibri, which was used to obtain results for the building model’s energy use, environmental impact and cost, for all possible renovation measures.

The evaluation process was conducted in three main parts. The first involved testing 1260 combinations of different passive renovation measures (i.e., improvements that don’t rely on active technology or mechanical systems, such as adding insulation or replacing the windows) 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.

• author: Baden, Nadja and Taghizadeh, Marziyeh
• supervisor: Ricardo Bernardo; Rafael Campamà Pizarro
• organization: Department of Architecture and Built Environment; Division of Energy and Building Design
• course: AEBM01 20231
• year: 2023
• type: H2 - Master's Degree (Two Years)
• subject: Technology and Engineering
• keywords: Optimisation, Parametric design, Decarbonisation, Renovation
• language: English
• id: 9130848
• date added to LUP: 2023-06-28 07:04:29
• date last changed: 2023-06-28 07:04:29