If we can calculate the risk better, it will allow us to move to a place to provide the transition to renewable energy, in a cost-effective way to the Danish society.

Einar Ritterbusch,, Head of Control Center Systems, Energinet

Business Challenge

By 2030, 100% of energy in Denmark must be generated from renewable sources, which fluctuate greatly and must be managed carefully. Energinet wanted to improve on predictive models to better manage the grid, reduce the risk of brown or blackouts and safely take equipment offline for maintenance.



Energinet teamed with IBM Services to pilot a multicloud solution based on IBM Cloud Pak for Data and Watson Studio that gleans operational predictions from big data using AI. A pilot tested the AI capability by simulating outages with known causes and remedies and comparing the outcomes with experienced operators’ conclusions. Operators are currently using the solution to help evaluate planned maintenance. Other uses include assessing grid operations, understanding system bottlenecks and suggesting cost-effective investments.


Solution Category

  • IBM Cloud
  • AI/Watson