„Planning Smarter Grids“ - Adaptricity's claim applies not only to individual, local networks, but also to large network areas with large sets of measurement data. What creates advantages on a small scale, only unfolds its full potential in the analysis and optimisation of large network areas with many more data points from electricity producers and electricity users. The benefits of a digitally planned, monitored and controlled grid area increase with the size of the area. Grid reliability increases while costs decrease at the same time. Es erstaunt deshalb nicht, wenn in der Energiepolitik als auch zunehmend bei den grossen Versorgern die Ambitionen bestehen, die Stromnetze ganzer Länder als Digitale Zwillinge detailliert abzubilden und für Netzanalysen und Netzbetrieb verfügbar zu machen.

And this "harnessing" of large amounts of data is next stage of digitalisation. The aim is to obtain detailed insights down to the lowest network levels - and thus almost complete network transparency. So that with just a few clicks it becomes visible when and where operational challenges such as network bottlenecks can arise in the entire network area. But not only that. By integrating real measurement data (transformer measurements, smart meters, PV production) into the grid model - depending on data quality and availability also by supplementing it with synthetic load profiles - the best possible digital representation of the grid infrastructure and its operation becomes possible. And this from the high-voltage level to the low-voltage house connection. This means that grid analyses and grid investments can be planned more precisely, more robustly and with numerous future scenarios . And there is no need to rely on often very rough grid models and many vague assumptions about grid operation, as has been the case in the past.

The following video illustrates this in a simple way: