Predicting Power Grid Overloads in Minutes Instead of Weeks

Challenge

One of Europe’s leading energy companies faced escalating grid congestion as energy transition and electrification drove connection requests beyond infrastructure capacity. Grid assets including high-voltage transformers and transmission lines operated at or near maximum capacity daily. Regional congestion varied significantly—some areas faced chronic overloads while others approached critical thresholds. Grid operators needed to manage current congestion while anticipating future bottlenecks, requiring integration of diverse datasets (grid models, investment plans, load data, flexibility inventories) and advanced analyses like load flow simulations. Analysis that previously took days or weeks delayed critical decisions on mitigation strategies including declaring congestion zones, offering flexible contracts, modifying agreements, and advising applicants on optimal locations.

Solution

We developed a cloud-native System for Automated Congestion Analysis that seamlessly integrates grid models, load data, and flexibility inventory into a unified analytical framework. The advanced analytical engine performs real-time load flow analysis, grid load predictions, and scenario simulations, delivering results in minutes instead of days. The scalable architecture supports national-level deployment with regional customization through reusable components. Stakeholder collaboration tools enable TSOs, DSOs, and regulatory bodies to share insights and coordinate decisions. The system provides instant forecasting for multiple years within seconds, supporting long-term strategic planning.

Business Value

Analysis timeframes reduced from days to minutes, enabling proactive congestion risk identification for multi-year planning horizons. Operators can evaluate mitigation strategies before bottlenecks become critical, optimizing infrastructure investments through predictive analytics. Data-driven insights support regulatory compliance and stakeholder communication. The system transformed congestion management from reactive problem-solving to proactive strategic capability, laying the foundation for a smarter, more resilient energy grid. The solution is now being considered for expansion to additional regions and use cases.

Download the full case study to learn how we implemented this transformational system in close collaboration with grid operators and regulatory bodies.

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