Visualising Building Occupancy in Brabrand to Improve Energy Planning

With occupancy data, you can get valuable insights for energy planning, as the way in which people use space (residential, public, commercial) directly affects building energy consumption.

In the BIPED project, we've started analysing, using GLayer, the building occupancy data to support demand forecasting across the Brabrand district of Aarhus. The data was taken from the Center Denmark Energy Platform and processed in an aggregate manner (250x250 meter grid) to overcome privacy restrictions. This approach ensured compliance with the GDPR while providing sufficient granularity for modelling purposes.

The data shows occupancy per target area as well as time window. This temporal aspect makes energy management more demand driven rather than based on static assumptions about when and how buildings use energy. For example, office loads tend to peak mid-morning, while residential homes peak in early mornings and evenings. By capturing these time-bound occupancy patterns, the energy system in Aarhus can better predict where and when energy loads will rise and adjust scheduling of HVAC, lighting, and appliances accordingly.

In the future, we would like to test some interesting cross-sectoral modeling scenarios by combining occupancy data with renewable energy datasets. The municipality is actively promoting greater rooftop PV coverage across Aarhus. Many residential homes and public buildings (e.g. sport centers, schools) now have solar panels that generate green electricity. Using occupancy forecast, on-site renewable production and storage can be optimally scheduled to meet expected demand so that, for instance, sufficient solar energy is stored for peak occupancy hours. This would reduce reliance on the grid, improving self-consumption and contributing to the PED development in Brabrand.