Trial / Demo
The EU-funded ENSNARE project, which has recently concluded, set out to accelerate deep renovation and decarbonisation of Europe’s building stock through innovative technologies. A key component was the development of a digital platform for operational optimisation, integrating physics-based digital twins with real-time data and advanced control strategies.
IES played a central role in this effort, providing the digital twin technology and optimisation workflow that underpin the project’s active control methodology. Using IES Virtual Environment (IESVE), the team created calibrated building energy models capable of simulating multiple operational scenarios to validate optimisation strategies before implementation.
ENSNARE’s pioneering approach has earned industry recognition: in October 2025, the project won Best Innovation Project at the A3E Energy Efficiency and Sustainability Awards in Seville, highlighting its impact on energy efficiency and smart building technologies.
This case study presents the results of the Tartu pilot deployment, which demonstrated the feasibility and benefits of an Operational Digital Twin, combining predictive modelling, Internet of Things (IoT) data, and human-in-the-loop automation. While the ENSNARE project has ended, the study in the Tartu building continues, providing valuable insights for future work.
Buildings account for around 40% of EU energy consumption, with heating and hot water dominating operational demand. Even after deep retrofits, operational energy use can remain high. Conventional Building Management Systems (BMS) are typically reactive and schedule-based, offering limited flexibility and optimisation. Retrofitting advanced control systems into existing buildings is often complex and costly.
The Tartu pilot aimed to overcome these barriers by integrating a physics-based digital twin with a cloud-based optimisation engine, enabling predictive, scenario-driven control without major infrastructure changes. The goal was to deliver measurable energy savings, maintain comfort, and prove the feasibility of human-in-the-loop automation.
At the heart of the project was the Building Operational Recommendation (BOR) service, a next-day optimisation tool designed to generate actionable control strategies for heating and cooling systems. BOR combines:
Recommendations are delivered via a secure web interface, enabling facility managers to approve or reject changes. This ensures that the automation remains under human oversight.
The pilot building is equipped with a BMS that integrates HVAC, solar thermal systems, and smart metering through open protocols such as BACnet, Modbus, KNX, M-Bus and CAN. IoT sensors provided real-time occupancy data, while a Honeywell Optimizer controller managed local operations.
The BOR service is connected to the BMS via the oBIX protocol, enabling secure read/write access to key control points such as setpoints and mode selectors. Two operational modes are defined:
During the testing period in the heating season at the beginning of 2025, the optimisation workflow ran daily. Time-series data was clustered to identify usage patterns, then processed through an optimisation engine to generate operational strategies. These were simulated in the digital twin and ranked using KPIs including energy use, cost, and thermal comfort. The best-performing scenario was sent to the facility manager for approval before automatic implementation.
The system operated successfully over a two-month winter period without disruptions or reported discomfort. Energy performance was assessed via weather-normalised models using Heating Degree Days.
When optimising modes accounting for occupancy, HVAC energy consumption dropped by a raw average reduction of 34%, rising to 50% post-normalisation. Marginal additional savings were realised through subsequent setpoint optimisation, while thermal energy output rose slightly (likely due to increased comfort setpoints on colder days).
Facility managers successfully approved recommendations through the web interface, which proved the viability of the human-in-the-loop approach.
The Tartu pilot demonstrated that integrating digital twins with BMS can deliver substantial energy savings without compromising comfort. By leveraging IoT data and predictive modelling, the system transforms building control from reactive to proactive, enabling day-ahead optimisation aligned with cost, carbon, and comfort priorities.
Key benefits include:
Although the ENSNARE project has concluded, the Tartu study continues, providing long-term data to test and refine the optimisation approach. The success of this pilot proves digital twin-driven control as a cornerstone of smart building strategies, paving the way for self-optimising, low-carbon buildings across Europe.
The ENSNARE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 958445. For more information on the project, visit the ENSNARE website.
