Good load management – the balance of electricity generation and consumption – is fundamental to the smooth running of decentralised grids. But stability is not solely dependent upon effective grid operations – it’s affected by demand and supply at the local level, by street and by household.

That’s why the Institute for Sustainable Energy Systems at the Munich University of Applied Sciences launched FLAIR in 2018, together with LEW Verteilnetz and Stromnetz Berlin, and developed a module for the automatic control of photovoltaic systems, heat pumps and charging stations in the local grid.

In FLAIR², the optimised module has been installed in a hundred households located between the Berlin electricity grid and rural southwest Bavarian network. From the six month field trial, the system has proved highly efficient at shifting consumption and mitigating peak loads. For example, electric cars tend to be charged in the evening at the same time as heat pumps, resulting in a peak load, so the smart module reacts to prevent the grid from overloading.

The decentralised load management system can also minimise “voltage jumps” that are caused, for example, when heat pumps or storage heaters switch off at roughly the same time. It prevents the simultaneous clocking of loads through flexible control, thus reducing strain on the network.

FLAIR²’s self-learning algorithms can analyse the grid situation locally and even create schedules for household consumption devices. The module is also programmed to adhere to the contractually agreed release and minimum charging times and can already be used within the existing legal-regulatory framework (§14a EnWG).

"We want a robust power grid that remains stable and functional even in the event of disruptions of communication – such as an internet connection," explains project manager Sonja Baumgartner from LVN in an article in PV Magazine. "We can achieve several goals at once: Avoiding bottlenecks, mitigating power peaks and making the system less sensitive overall.”