Dlaboratory Sweden AB (publ) provides a powerful platform for collecting, analyzing, and contextualizing grid data. Every day the platform records thousands of deviations that are further processed and analyzed by the dInsight Analytics Platform.

Thanks to both the sensitive and high-resolution measurement, even the smallest ripple in current and voltage waveforms are recorded. These registered data are further classified individually to one of a set of defined categories, where some are disregarded as minor disturbances without individual significant value and hence unclassified. However, all data including these unclassified ripples has always been stored for future purposes.

Today, these ripples have proved to be very important in dLab’s next endeavors towards the perfected grid insight.

By applying machine learning algorithms on so called time series including both classified and unclassified data, patterns not visible to either the human eye or advanced signal processing have been detected. The results strongly indicate a possibility to with high accuracy automatically predict serious faults hours in advance when taking theses previously unclassified data into account.  

So, what implications could this have for your supply quality?