Analysis and decision support for distribution grid capacity reinforcement

Minimizing risk in long-term power grid capacity investments

  • Predicting demand

    Dynamic, time-series predictions of future demand based on large historical datasets

  • Identifying bottlenecks

    Causal bottleneck identification based on dynamic load simulations

  • Offering solutions

    Recommendations of suitable interventions, including recommendations for type, dimension, location and cost

  • Estimating cost/benefit

    Cost/benefit calculations for each suitable intervention related to grid-, market- and societal benefit

Our mission

Leveraging big data and machine learning to identify flexible and cost-effective alternatives to grid expansion.