Intelligent energy management optimizes power consumption in buildings
Researchers at the Swiss Federal Laboratories for Materials Science and Technology (Empa) have developed an automated system that controls the production, feed-in and consumption of renewable energy in a building and saves CO2. It was tested at NEST in Dübendorf.
A predictive control algorithm developed by Empa optimizes energy management in buildings in such a way that security of supply is guaranteed throughout the entire energy system. Automated building systems communicate directly with energy providers and the power grid.
According to a report by Empa, automated systems can optimize electricity consumption in such a way that both grid stability and consumer flexibility are guaranteed at all times. At the same time, energy surpluses are not necessarily stored locally, but fed into the power grid wherever possible so that demand can be met at all times.
During the practical test by Empa’s Urban Energy Systems Lab in its NEST test building in Dübendorf, the focus was on reducing CO2 emissions, the flexibility of energy demand and the comfort of the residents. Using the predictive control algorithm, the team succeeded in optimizing energy management within the building with the following setup: a photovoltaic system for electricity production, a battery storage system, a heat pump and a bidirectional charging station for electric vehicles.
The system reportedly reduced the building’s CO2 emissions by more than 10 percent. The building was able to communicate the consumption and feed-in of electricity in advance. “The experiment has therefore shown that the flexible availability of renewable energies is not a problem a priori,” says Empa.
However, in order to implement these results on a large scale, buildings will have to be consistently digitalized in the future. The technology developed by scientist Federica Bellizio is to be brought to market by the start-up Kuafu. She was recently awarded the Empa Entrepreneur Fellowship for her work.