Saving energy in buildings with a digital twin.

From ambition to control over energy consumption

A national real estate organisation wanted to reduce the energy consumption of hundreds of buildings while meeting stricter climate policy. Teams were looking for more control over the performance of installations and a way to influence consumption in time. Existing systems mainly provided insight after the fact, which limited optimisation. The organisation therefore sought a practical approach that predicts what a building needs and makes energy-intensive processes work together better. Comfort for occupants had to be maintained, while management could not become more burdensome. Facilitech helped make these ambitions concrete and find a suitable digital approach. Based on the organisation's wishes and context, Facilitech chose to deliver a digital twin that provides insight into energy performance and helps adjust at the right moment.

A digital twin that predicts building performance ahead of time

Together with Priva, Facilitech delivered a digital twin that brings all relevant data about a building together in a single overview. The application combines energy flows, occupancy, weather forecasts, generation and storage, making it clear where energy is needed and where consumption can be reduced. The digital twin predicts energy demand up to 24 hours ahead and automatically adjusts climate systems, so the system keeps improving itself. Anomalies are spotted early, preventing failures and making maintenance predictable. Building managers and maintenance contractors then track performance through clear dashboards, so decisions are based on facts. The collaboration resulted in a practical application that fits daily management in a single overview and scales easily to other buildings, without added complexity.

Visibly lower consumption and predictable performance

By using AI and digital twin technology, the organisation expects to achieve energy savings of up to 40 percent and structurally reduce CO2 emissions, taking major steps towards its climate targets. The system also contributes to a more stable and comfortable indoor climate, leading to higher occupant satisfaction and fewer complaints. Predictive control means installations are used more efficiently, wear decreases and maintenance costs fall. The investment is expected to pay for itself within two years, making the business case particularly attractive. In addition, the digital twin provides a solid foundation for further optimisation and a phased rollout to other buildings in the property portfolio, so that sustainability and cost control go hand in hand with innovation and future-proof property management.