Cognitive IoT Framework for Building Energy Optimization (CBEO)


To achieve the proposed operational functionalities in REN+HOMES, multiple technological developments are required. A modular platform will be developed to solve conflicting requirements, be it cost reduction, enhanced comfort, or finding an optimal balance. The platform will also detect and notify users of non-optimal energy states, such as unoccupied spaces or open windows, using an optimal energy management engine.

Target technical data

Maintenance and operation cost savings


Total cost reduction vs typical construction/retrofitting


State of the art and main challenges

Several tools exist to satisfy diverse user desires, like thermal comfort or energy costs. However, current buildings do not harmonise these tools, which can make them work against each other sometimes. Potential advancement requires the optimization of energy grid demand and tailored consumption-generation management.

Innovations and added value

There will be several technological developments to achieve the operational functionalities proposed in REN+HOMES. The solution will be modularised to cover a wide range of potential needs, whether for minimising costs, maximising comfort, or achieving an optimal balance between the two. Non-optimal energy states (e.g. no human presence/ open windows etc.) will be also detected and the optimal energy management engine will provide notification of this. Further advancing the capabilities of the CBEO, the platform will be made ready to support energy flexibility requests from external parties using industry standard protocols. As such, the user will be able to select between utilising flexibility for own consumption or grid support purposes. A novel flexibility characterisation algorithm will be developed to enable the fine-grained flexibility determination, in terms of shiftable demand and comfort loss. Finally, the CBEO price forecasting module will take into account different energy pricing contexts in the different pilot countries.