2 citations · 2 across the 3 of their papers we have counts for
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cs.LG2022★ 2 cited
Probabilistic forecasts of wind power generation in regions with complex topography using deep learning methods: An Arctic case
Odin Foldvik Eikeland, Finn Dag Hovem, Tom Eirik Olsen +2
The energy market relies on forecasting capabilities of both demand and power generation that need to be kept in dynamic balance. Today, when it comes to renewable energy generatio…
cs.LG2021
Detecting and interpreting faults in vulnerable power grids with machine learning
Odin Foldvik Eikeland, Inga Setså Holmstrand, Sigurd Bakkejord +2
Unscheduled power disturbances cause severe consequences both for customers and grid operators. To defend against such events, it is necessary to identify the causes of interruptio…