In this project, industrial and research partners will explore the potential of advanced data analytics to support the renovation challenge of the existing residential building stock by focusing on the digital twin concept. The digital twin concept will be investigated as an enabler to support informed decision making for different stakeholders in the residential sector (cities, social housing companies, home owners, …). We will do this through profiling, clustering and filtering, offering more interesting business cases on both ends of the renovation market spectrum.

Status

Running project

Period

-

In Europe, almost 40% of the building stock predates 1960 and was not built according to any energy efficiency plan. Therefore, an intelligent and ‘deep’ renovation of residential buildings would enable considerable energy - and CO2 emission reductions. However, the traditional and fragmented market and the lack of ‘renovation packages’ in Flanders, make it a challenge to meet European and national goals: the current renovation rate is only about 1% per year. To reach the CO2 reduction ambition, a 3% annual renovation rate should be achieved. Identified blocking factors to achieve this renovation rates are, lack of incentives, high costs for renovations, decreasing contractor work force, missing ambition in the legislative framework for renovations, etc. Crucial blocking factors can be reduced to the benefit of contractors, governments, home owners and renters by making efficient use of new and existing data sources, resources (man hours, material, equipment, ...), adequate planning (clustering, combining works, …) and well targeted incentives.

Within this project we want to develop a digital twin concept for upscaled retrofits. Additionally, a user engagement proof of concept will be built around this to best serve the different stakeholders related to the challenge of upscaling retrofit. We will test this approach with two different target groups: urban environment and social housing companies. A data management plan will be drafted to deal with the legislative framework. This project will also report on the potential of scaling up to a broader perspective considering insights from consultations with society including the value network and business model for digital twin concepts in Flanders.

The project aims for an accuracy of 5-10% of the recommended renovation bundles and 5-10% accuracy of the cost estimate of the renovation (compared to individual audits); wants to proof that 60% of the dwellings in cities are eligible for an energy-based renovation and that 30 to 40% of the concerned dwellings can be renovated by means of a mass renovation approach, achieving a cost reduction of 20 to 25% compared to an individual renovation while increasing the speed of renovation with 20% and limiting the discrepancies between predicted and actual effectiveness of the renovation to 10%.

Role of EnergyVille/VITO

The state-of-the-art research that EnergyVille/VITO executes in this project is:

  • Investigate the impact of improved building characterization on energy retrofit advice
  • Incorporate different data streams in city planning for upscaling the renovation potential based on open data and new to acquire data stream about the building characteristics, dimensions, installations and user behavior, co -benefits (comfort, increased building value,) …
  • Link the demand and supply through an integrated data approach based on the renovation need and contractors offerings.
  • Investigate the potential for stepped approach renovations and clustering of different similar renovation projects avoiding lock in; and define optimal renovation packages by testing our predictions in the field after implementation on building level.
  • Investigate the limitations of data gathering approaches, visualizations on city scale and data transfers between different partners
DITUR