Is it possible to reliably predict voltage anomalies in the power grid minutes in advance using machine learning models trained on large quantities of historical data collected by power quality analysers (PQA)? Very little previous research has been done on this topic. To investigate whether this is...

Power supply disruptions, including short-time disturbances, can lead to large direct and indirect financial losses. The ability to predict the risk of these disturbances allows for preventive actions and increases the reliability of the supply. This paper investigates the impact of using season...

Data for store feil i nettet og historiske værmeldinger er brukt for å se hvilke parametere som mest relevant og om det er mulig å predikere feil. Presentasjon ved Volker Hoffmann. Delaktivitet i forskningsprosjektet Energytics. Https://www.sintef.no/prosjekter/energytics/...

Automated detection of EVs from smart meter data can provide important insights for DSOs about spatiotemporal EV charging patterns. However, smart meters typically provide only hourly measurements of consumption while most load disaggregation techniques require at least minute level data. We use mac...