In Germany, the building sector accounts for more than one third of the total energy consumption. It therefore comes as no surprise that efforts to increase energy efficiency and reduce energy consumption in the context of the energy transition are being specifically targeted.

One way to achieve this objective is to strengthen the intelligent linking of energy supply and demand ‒ in real time. A prototype of an energy management system developed as part of the Federal Ministry for Economic Affairs and Energy (BMWi)-funded research project “DENU ‒ Digital energy use for increasing energy efficiency through interactive networking” is intended to show that this is possible. The innovative system is not only typified by a holistic view of the energy flow in a building complex, but also, among other things, by using weather forecasts as well as independently implementing recommendations for action derived from them.

Under the direction of the Landshut University of Applied Sciences, data will be collected on the energy flow in various types of building such as hotels, indoor swimming pools or administrative and factory buildings. Machine learning is then used to analyse the data base, which is supplemented by historical data. On this basis, algorithms are developed that are able to intelligently control the energy flow in buildings. In doing so, they consider all the numerous potentials for reducing energy consumption, for example by reducing the flow temperatures of heat generation systems when the weather is fine or by using surplus solar power for producing hot water.

By 2022 an energy management system is to be designed that can halve the primary energy consumption in buildings in future. The project has been granted over 1.4 million euros in funding by the BMWi within the framework of the 6th Energy Research Programme.