PEKIVE

The project has demonstrated that it is possible to gain significant energy savings and make large non-residential buildings energy-flexible, by implementing AI-based solutions for predictive energy management.

The representative buildings that participated in the project, showed better indoor climate, lower consumption (up to 26% in a specific month) and a technological ability to interact with dynamic electricity prices and CO2 emissions from electricity production in the grid. This is done by connecting a cloud-based solution to already installed BMS systems with open interfaces.

To be able to monitor impact of such solution, a simple tool to document outcome and key performance indicators have been developed using simple IoT sensors and energy data available from the cloud or from the specific utility.

Specific barriers for accelerated implementation in larger building portfolios have been identified and listed.

The findings have also been addressed to the market segments through several workshops, involving building owners, building operators and energy consultants, resulting in new solution providers in the market. By having cases that can be used for demonstrations, consultants that knows pros and cons and system integrators willing to implement new technologies, this kind of AI-driven solutions is expected to be implemented by more building owners.

Recordings and key take-aways from workshops is available on the project website www.energifleksiblebygninger.dk