We collect building-level demand and potential data, store it securely in modern GIS databases and visualize it in meaningful maps. This makes complex relationships visible – and informed decisions possible.
Data-driven energy planning – transparent, illustrative, interactive.
Data-driven – precise analyses, founded concepts
Future-proof – resilient and adaptable to different scenarios
Participatory – together with all stakeholders
Technologically leading – AI-powered
Enpageo emerged from the EnergyMap Berlin research project funded by the Federal Ministry for Economic Affairs and Climate Action (BMWK). In this project, a building-level digital heat cadastre for Berlin's building stock was developed. The heat cadastre, available to the public, displays forecasts of heat consumption for individual buildings. The cadastre includes several hypothetical renovation scenarios as well as a selection of optimistic and pessimistic climate scenarios for the coming decades. For the entire Berlin building stock, building-level heat demand simulations were created using 3D building models and publicly available data, and these were subsequently calibrated with real consumption data. Several AI forecasting models were trained so that interested parties can adjust their building data if necessary and receive an updated heat consumption forecast in real time. Try it yourself – visit EnergyMap Berlin now!
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