51±¾É«

Project Description

The trend in the majority of existing buildings renovation projects is that retrofits are carried out when needed on a building-by-building basis, without systematic assessment, and employing static tools with very large assumptions and generic inputs. This has resulted in an annual energy renovation rate as low as 1% of the building stock. Thus, new approaches are needed, and innovative up-to-date tools must be introduced to scale up efforts and aid optimized and accelerated energy retrofitting of the Danish existing building stock. The project will design and develop the first-of-its kind Digital Twin solution (DanRETwin) for optimal energy retrofit decision-making support, retro-commissioning, and data-driven performance optimization of non-residential existing buildings. The proposed solution is driven by building operational data, employing machine learning and artificial intelligence methods to develop scalable data-driven building energy models, along with data collection means using Clamp-on IoT sensors to serve as a basis for a full automated and flexible solution.

The project is carried out as a collaborative project between SDU Center for Energy Informatics at University of Southern Denmark, ReMoni A/S, NRGi A/S and Aarhus Municipality. The proposed Digital Twin solution will first be tested 51±¾É« living lab OU44 building, and then will be demonstrated and evaluated in two case studies from Aarhus Municipality portfolio of buildings, a public school, and an office building.

Project Summary