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DecabonAIte

network and connection concept with cityscape as background, business concept, vintage style process

DecarbonAIte is a three-year project funded by VINNOVA to develop digital tools and methods for large-scale energy renovation of buildings.

Large-scale energy renovation of buildings is needed to meet climate targets by 2045. Developing digital urban twins can provide the basis for renovation planning and provide good decision support, so that the right prioritization and best actual measures are taken during the renovation.

Areas of work of the project

The project adapts and applies machine learning (ML) and AI in different ways and has the following main areas of deliverables:

  • From public databases, geometry data is extracted to build a digital twin of the building. In order to work with the twin, it needs to be enriched. The project is therefore developing methods to extract information for performance simulation of the building. It can be information for complete 3D geometry such as window and roof design, building materials, etc. Methods for obtaining the information range from ML through image recognition to the collection of actual information about the building.
  • Information on energy use or more technical info, such as u-values of the windows in the building can be obtained from the real estate companies in the project whose buildings serve as case studies.
  • The project then develops optimization methods based on Genetic Algorithms for energy simulation, Life Cycle Assessment (LCA) and Life Cycle Cost Analysis (LCC). This creates opportunities to "calculate" optimized interventions.
  • The project finally implements the optimization methods in a decision support tool to be used by the need owner. This can be from large property owners to entire municipalities. The decision support tool is tested and evaluated by the real estate companies in the project's three case studies.

The project will provide managers and municipalities with a better digital platform for building management. In the long term, the project will help to increase the pace of renovation and achieve climate goals. The enriched digital twins are also expected to provide benefits beyond renovation planning, for example for the planning of energy production in the municipality.

Results from the project

Here you can watch three videos that describe the results achieved within the project: West Sweden Energy Agency - DecarbonAIte

About the project

Our roleProject leader
Project ownerChalmers Industriteknik Foundation
Funded by VINNOVA Swedish Innovation Agency

Project partners

Chalmers University of Technology, Sofia University, ETH Zurich, Sinom AB, Asymptotic AI AB, City of Helsingborg, EkstaBostads AB (Kungsbacka) and Uddevallahem

Contact us

Peter Berg, Innovatum Science Park

Peter Berg

Innovation Leader Renewable Energy

Funded by