Case Study: Energinet achieves faster renewable integration and enhanced grid resilience with IBM Cloud Pak for Data

Northern Europe’s Energy Hub Looks to IBM Garage and Cloud Pak for Data to Design a Green Energy Future

Energinet, Denmark’s transmission system operator serving 5.8 million citizens and targeting 100% renewables by 2030, faced the challenge of maintaining grid resilience and security of supply amid unpredictable weather and fluctuating cross-border flows. To better predict risks and support operational decisions across massive simulation datasets (about 400 terabytes), Energinet engaged IBM Garage and used IBM Cloud Pak for Data in a three-month pilot to design a “virtual operator” for scenario modeling and risk estimation.

Using IBM Cloud Pak for Data, the team deployed a hybrid cloud architecture and Watson Studio Machine Learning to train models on terabytes of N‑1 historical simulation data and deliver a user interface that shows risk probabilities, generates look‑ahead scenarios, and supports the Operations Center. The solution processed ~400 TB of simulation data, enabled rapid what‑if analysis (including equipment outages), improved maintenance prioritization and decision-making, and gave Energinet a scalable, ML-driven decision‑support capability as it moves toward a green energy future.

Energinet