The Empa spin-off “viboo” has developed a self-learning algorithm to control the indoor climate. This allows buildings to be cooled or heated in advance, saving around one-third of energy. Following successful experiments in NEST, the research and innovation building of Empa and Eawag, the first pilot projects are now being implemented with industrial partners.
Conventional thermostats, which are installed in many residential buildings today, only react when the temperature falls below or exceeds a certain threshold. The reaction is therefore always too late and only then abrupt and violent, since the desired temperature is to be reached again as quickly as possible. This costs energy and ultimately money. The solution: a thermostat that looks into the future and regulates the temperature in advance.
Looking ahead to save energy
A spin-off of Empa, which is currently in the start-up phase, provides a glimpse into the crystal ball. The company calls itself “viboo,” which stands for “viable intelligent building operation optimization.” In the course of their research at Empa, founders Felix Bünning and Benjamin Huber have developed an algorithm that allows buildings to be controlled predictively. The amazing thing is that only two weeks’ worth of building data, such as valve positions and room temperature measurements, are needed to create a model of the building. In combination with predictions of the local outdoor temperature and global solar radiation, the algorithm then independently calculates the ideal energy input to heat or cool the building up to twelve hours in advance. This eliminates hectic, reactive controls, which requires significantly less energy.
“The potential is enormous. Our experiments at NEST have shown that this approach can achieve energy savings of between 26 and 49 percent,” explains Felix Bünning. The researchers used the Research and Innovation Building on the Empa campus to test and further develop the algorithm in a real-world environment. The field tests generated interest from industry, and the researchers realized that their algorithm should be taken from research to market.
The motivation of the two scientists is not financial, but rather social. “An enormous amount of energy is used worldwide for heating and cooling buildings. This is one of the reasons why the building sector accounts for a large proportion of global CO2 emissions. With our algorithm, we want to help as many households as possible to save energy and thus make our contribution to reducing these emissions,” says Bünning. An initial funding initiative has already recognized that this project makes sense. In November 2021, “Venture Kick” awarded “viboo” a grant of 40,000 Swiss francs. In addition, Bünning is supported by a “BRIDGE Proof of Concept Fellowship” from the Swiss National Science Foundation and Innosuisse.
Pilot project for smart control
“We are currently focusing on manufacturers of thermostats for residential buildings. Many of these companies already have smart thermostats in their portfolio. By means of a cloud connection, we can integrate our algorithm into them,” explains Felix Bünning. A first partner is the internationally active thermostat manufacturer Danfoss. Together with the company, “viboo” is now implementing the first pilot project in a conventional building. In the process, the thermostats in Empa’s administration building will be replaced by smart thermostats running the “viboo” algorithm. Based on the indoor climate data, this first creates the building model. After that, the algorithm takes over the control of the heating for four months. The central question is: How efficiently does the algorithm regulate compared to the standard solution? This will provide information on how high its potential is in conventional, older buildings.
In addition to the pilot project, however, talks are already underway with other industry partners to explore further potential applications. “viboo” will, for example, integrate the algorithm directly into the building automation system in a new building in Zurich, optimizing control throughout the office building.
