immo!nvest – Die Plattform für Standorte und Immobilien

Tag: Algorithmus

  • Buildings contribute to grid stability

    Buildings contribute to grid stability

    The transformation of the energy sector brings challenges. Renewable energies such as photovoltaics do not provide a constant supply of electricity, but are subject to weather conditions and times of day. The power supply must therefore become more flexible in order to utilise production peaks and compensate for bottlenecks. This is precisely where automated building systems come in. They control consumption and feed-in intelligently and reduce the load on the grid.

    Predictive control for maximum efficiency
    An innovative algorithm developed by Empa analyses energy availability and user behaviour in order to optimally control energy consumption. For example, surplus solar energy is prioritised or stored instead of overloading the grid. At the same time, comfort is maintained. Hot water or heating are available exactly when they are needed.

    Successful practical test in the NEST building
    The algorithm was tested under real conditions in a pilot project in Empa’s NEST building. A photovoltaic system, battery storage, a heat pump and a charging station for electric vehicles were used. The results show that CO2 emissions were reduced by more than 10 per cent without compromising user comfort. The building was also able to communicate independently with the grid in order to absorb peak loads.

    Digitalisation as a prerequisite for scalable solutions
    The study shows that intelligent energy control is a key building block for a sustainable energy future. In order for such solutions to be used across the board, consistent digitalisation is required. At the same time, it must be ensured that the IT infrastructure remains sustainable. Empa researchers are therefore already investigating ways of using old smartphones as control units for building automation.

    The future of energy supply lies in the networking of intelligent systems. Through predictive management, buildings can not only cover their own energy requirements, but also actively contribute to grid stability.

  • Viboo wins Empa Innovation Award

    Viboo wins Empa Innovation Award

    Every two years since 2006, Empa has honored in-house innovations or successful technology transfers from science to industry with the Empa Innovation Award. This year, the CHF 5,000 prize went to the Empa spin-off viboo , the research institute said in a statement . The young company based in Dübendorf has developed a self-learning algorithm that uses weather and building data to calculate the optimum energy use of a building several hours in advance.

    The algorithm developed by Felix Bünning and Benjamin Huber together with Empa Senior Researcher Matthias Sulzer in Empa's Urban Energy System Lab has already been tested in pilot tests in the NEST innovation building and in an Empa administration building. It has been shown that the approach can save around a quarter of the heating energy, according to the statement.

    For the application, only the analogue thermostats have to be replaced by intelligent thermostats. Here, viboo is already working with Danfoss and wants to get other manufacturers of such thermostats, such as ABB and Schneider Electric , on board for further pilot projects. Huber wants to reciprocate the award with a contribution that “empa will get through the coming heating period well”, the viboo co-founder is quoted as saying in the press release.

  • viboo saves heating energy with a learning algorithm

    viboo saves heating energy with a learning algorithm

    viboo has developed an algorithm to save heating energy. According to a press release , the spin-off of the Federal Materials Testing and Research Institute ( Empa ) can also heat older buildings with around a quarter less energy. The user comfort remains the same or even improves.

    Researchers Felix Bünning and Benjamin Huber developed the idea while working in Empa's Urban Energy Systems Lab. Based on weather and building data, the control algorithm can calculate the ideal energy consumption of a building several hours in advance. The first experiments in NEST , Empa and Eawag 's research and innovation building in Dübendorf, reduced energy consumption by 23 percent. The researchers worked together with the thermostat manufacturer Danfoss . In comparison, the Danfoss Ally thermostat saved only twelve percent.

    In March 2022, the two researchers founded viboo together with Matthias Sulzer, Senior Researcher at Empa, to bring the solution to market. In the next heating season, the company will carry out further test projects, apart from with Danfoss also with other manufacturers such as ABB and Schneider Electric .

  • An algorithm controls thermostats

    An algorithm controls thermostats

    Two researchers from the Urban Energy Systems Lab at the Swiss Federal Laboratories for Materials Testing and Research ( Empa ) have created a self-learning algorithm for heating thermostats. According to an Empa report , it can be integrated into conventional intelligent or smart thermostats via a cloud connection and regulate the room temperature in a predictive manner.

    "The potential is enormous," says Felix Bünning, co-founder of the Empa spin-off viboo, which markets this algorithm. "Our experiments at NEST have shown that energy savings of between 26 and 49 percent can be achieved with this approach."

    To create a model of the building, building data such as valve positions and room temperature measurements from just two weeks are sufficient. In combination with forecasts for the local outside temperature and global solar radiation, the algorithm then independently calculates the ideal amount of energy required to heat or cool the building up to twelve hours in advance.

    According to the information, a first partner is the Danish company Danfoss . The internationally active thermostat manufacturer is currently testing in a pilot project together with viboo how high the savings potential is in conventional existing buildings. In addition, the start-up is already in talks with other industrial partners. For example, it will integrate the algorithm directly into the central building automation system in a Zurich office building.