A new developed smart home lighting control system is demonstrated in SAB Housing Association Department 75 in Sønderborg, DK. The demonstration site includes 19 double terrace houses, in total 38 apartments. The smart home systems in the apartments control the lighting, electrical appliances, access controls and burglar alarms. The electrification control system can also be connected to the heating control system. 

Remotely from a smart phone app, the user can turn on and off each lighting unit and electrical appliance in the apartment and control the temperature of the heating system. The regulation can also be activated from a central panel placed on a wall in the apartment.  

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Danfoss Leanheat Building is an AI-based software and control system used to manage heating at building level. It replaces the traditional approach based on a fixed relationship between heating supply temperature and outdoor temperature, known as weather compensation. Instead, the solution combines an adaptive dynamic building model with weather forecasts and measured indoor temperatures from apartments. This allows the system to estimate the optimal heating supply temperature at any given time while maintaining indoor comfort, taking into account the building’s passive thermal storage capacity as well as solar radiation, wind, and outdoor temperature predictions.

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This solution explores the integration of a low-exergy ground-source heat pump with Thermally Activated Building Systems (TABS) to deliver efficient heating and cooling in buildings, focusing on a pilot site in Oslo. While TABS enhance energy efficiency by leveraging the thermal inertia of concrete structures, their slow response time currently leads to poor indoor comfort due to inadequate rule-based controls. To address this, a room-level Model Predictive Control (MPC) system is proposed to improve temperature regulation using data-driven models continuously trained during building operation. Additionally, a building-level MPC will coordinate various systems to optimize energy costs, implement demand response strategies, enable fuel switching, and maximize on-site solar PV self-consumption. These smart controls use forecasts of weather, occupancy, energy prices, and PV output.

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