Self-learning predictive control through physics-informed Machine Learning

Award-winning technology

Every two years Empa gives the Innovation Award in recognition of outstanding innovation and technology transfer projects. The prize honors excellent innovations or a successful technology transfer to industry. In 2022, the award was given to viboo co-founders Felix and Benjamin.

Outstanding doctoral theses are honoured with the Silver Medal of ETH Zurich. The medal is awarded to less than 8% of all theses submitted. It was awarded to co-founder Felix, whose research is the foundation of viboo’s technology.

During the Swiss Digital Days 2022, 60 sustainable project ideas from driven entrepreneurs that preserve and protect natural resources competed at the “GreenTech Startup Battle”. viboo won the final and took home the award.

Self-learning predictive control ...

We use a combination of Machine Learning methods and building physics to generate thermal building models purely from measurement data. Compared to conventional Model Predictive Control, no manual modelling is necessary. Compared to pure Machine Learning based methods, the inclusion of building physics ensures that the model has physical behaviour and reduces the training time to 1-2 weeks.

The generated models are used in a predictive control framework, which predicts the thermal behaviour of the building for the next couple of hours, considering the weather forecast. Taking into account user preferences, occupancy schedules and operational constraints, the optimal energy input for the building is calculated every few minutes and send to the building.

... validated in actual buildings.

We have validated the method in residential and light commercial buildings for heating and cooling operation, where it saves between 20% and 40% of energy compared to a state-of-industry controller. As the controller anticipates changes in weather, it also improves comfort, because it can act proactively.

Besides advantages in energy consumption and comfort, the method can exploit time-varying energy prices efficiently and is already ready for demand response schemes, which will become more and more relevant with more renewables entering the electricity grid.

Demonstrated at Empa in Switzerland