Mission

To operate a modern electricity grid with high renewable penetration and decentral flexibility, system operators need forward visibility on both expected power flows and grid topology. Nodis supported the implementation of AI-driven short-term forecasting combined with a digital grid twin, enabling operators to anticipate grid behaviour and act proactively in operations and markets.

Objectives

• Anticipate grid behaviour
  Provide near real-time visibility on future adequacy, balancing risks, congestion and voltage issues.

• Support operational and market decisions
  Determine reserve needs, grid losses and sourcing strategies based on reliable forecasts.

• Create a reliable system model
  Establish a single source of truth for load, generation and storage assets and continuously update & forecast system snapshots for simulations from near real-time to long term future timeframes.

• Deploy modular hybrid software architecture
  Combine custom built solutions around proprietary grid simulation software to increase flexibility, enable parallel development and avoid vendor lock in.

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Our contribution

Nodis delivered the functional and architectural backbone of the platform:

• Technical leadership and project coordination
• Business & functional analysis and solution architecture
• Design of data models, validation logic and integrations
• Steering iterative implementation and quality delivery

The result is a reliable decision-support environment combining forecasting and simulation for proactive grid management.

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