Increasing Energy Efficiency in Buildings Using AI

The Predictive Company has developed an energy efficiency software based on artificial intelligence for non-residential buildings that connects the internal data with external variables, creating a digital twin. A connection is made to the BMS (or SCADA system) of any building and from there, the necessary data to run our program is extrapolated. An accurate prediction of the building’s energy need is made, and the HVAC (heating, ventilation, air conditioning) machinery is optimised and automatised.  This results in energy savings and a reduction in CO2 emissions of up to 30% for any building.

The following are examples of successful implementations of our solution: 

• Implementation of solutions in bank office, Potosi, which belongs to the Caixa d’Enginyers. TPC conducted an in-depth analysis of the building’s energy performance with particular emphasis on their HVAC performance. Both external and internal factors were considered by our intelligent algorithms after making a connection via the BMS of the building.
• The second implementation was in a University Building, GAIA, located at the Polytechnic University of Catalonia in Barcelona. Areas of improvement were identified in their HVAC system, and external and internal variables were again combined to gather information about the building’s unique characteristics and energy needs. Through remotely and automatically controlling climate machines through an OPC (open platform communication), our solution resulted in hugely positive consequences for this building.