DecarbonAIte

Important results from the project

The project developed and tested a model for optimizing renovation options, validated on a large dataset. A pipeline for digital twins and an AI model for energy calculations were also created. The methods enable cost-effective, climate-friendly renovations on a large scale. Several tools are planned to be used in future projects.

Expected long term effects

The project demonstrates that optimization-based analyses can be used to identify renovation options that are both cost-effective and reduce climate impact. The results also indicate that these methods can be scaled up for use at city or regional levels, enabling more strategic and efficient renovation planning. Several of the tools and methods developed in the project will be further developed and applied in future research projects.

Approach and implementation

The project was carried out as planned despite challenges that affected the timeline. The work was organized into three main activities, run in parallel by Chalmers, CIT, and Asymptotic. This structure contributed to efficiency in the development work but also led to some integration challenges in the final phase. At times, this made it difficult for stakeholders to follow the progress and gain sufficient insight into the development.