Electrification
Demand patterns are changing as heat, transport, industry, and AI data centers connect to the grid.
Startup from Delft AI Energy Lab
Foundation Models for Power Grids
Hypernode builds the intelligence layer for energy systems, enabling faster, more accurate, and scalable operational decision-making for grid operators.
POCs developed at Delft AI Energy Lab Sovereign model training Grid-operator workflows
grid_statesecure
scenarios4,096
latencyinference speed
The current grid reality
The Grid Is Reaching Its Limits
Electrification, renewables, data centers, and congestion are pushing existing operational tools beyond the scale and speed required by grid operators.
The European grid illustrates why operational intelligence must reason across topology, physics, uncertainty, and constraints at continental scale.
Congestion
Connection queues and operating constraints are becoming a board-level issue for grid operators, industry, and customers.
Rising costs
Operators need better decisions before congestion-management costs compound into double-digit billions.
Operational limits
Existing workflows were not designed to evaluate thousands of contingencies, actions, and uncertainty states fast enough for modern operations.
Why existing tools fail
Existing Grid Models Cannot Scale
Combinatorial complexity
Thousands of substations, lines, constraints, contingencies, and remedial actions interact across time.
Uncertainty
Weather, renewables, demand, outages, and markets move faster than deterministic workflows can absorb.
Fragmented software
Planning, forecasting, security assessment, and dispatch still rely on disconnected tools and manual handoffs.
The Hypernode platform
A Foundation Model Platform for Energy Systems
A modular platform for power grids that turns lab-validated proof-of-concepts into operator-grade decision support, without forcing sensitive operational data to leave the operator context.01
Grid data
SCADA/EMS snapshots, topology, asset status, weather, and market context.
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Synthetic data layer
Curated and anonymized representations that preserve sovereignty.
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Foundation models
Models that learn grid physics, topology, and operational behavior.
04
Inference engines
Power flow, scenario generation, market, weather, and decision-support engines.
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Applications
Congestion management, security assessment, forecasting, and operational planning.
Operator workflow day-ahead decision support
01 Scenario generation
Explore thousands of weather, demand, market, and topology states.
02 Fast grid inference
Screen operating limits, flows, and constraints at model speed.
03 Ranked actions
Compare topology, redispatch, and flexibility options with technical and cost-benefit context.
Why foundation models
The Next Wave of AI for Energy Systems
Learn grid physics
Capture topology, constraints, and physical system behavior instead of treating the grid as a generic dataset.
Preserve data sovereignty
Train and fine-tune from synthetic representations without requiring operators to share sensitive grid data.
Accelerate decisions
Run simulations at AI inference speed, so operators can explore uncertainty before acting.
Applications
Callable Engines or Stand-alone Operator Apps
Start with high-friction workflows in transmission and distribution operations, then expose foundation models through APIs that can integrate into existing control-room and planning environments.Congestion management
Evaluate remedial actions, topology changes, costs, and operational feasibility across thousands of scenarios.
Security assessment
Screen contingencies and system states with fast model-assisted analysis.
Forecasting
Combine weather, renewables, load, and grid state to support operational foresight.
Operational planning
Bridge planning and control-room workflows with consistent model infrastructure.
Early validation
Built with the Grid Ecosystem
Hypernode Labs is a startup emerging from Delft AI Energy Lab. The initial proof-of-concepts were developed there, and the methods are being validated in collaboration with Alliander and TenneT. The focus is practical: operator workflows, data sovereignty, and integration with the tools grid companies already use.
Delft AI Energy LabTU DelftAllianderTenneTGridFM ecosystem
15+ years of research
POCs from Delft AI Energy Lab
Validated with Alliander & TenneT
European grid ecosystem
About
Built by Power-System Researchers and Infrastructure Builders
Hypernode Labs is a startup coming from Delft AI Energy Lab, where the first proof-of-concepts were developed. The team brings together power-system research, AI engineering, optimization, synthetic data generation, and experience building mission-critical software for industrial environments.Power-system depth
The company is rooted in Delft AI Energy Lab and 15+ years of power-system and AI research.
Research to deployment
Proof-of-concepts were developed in the lab and are now being translated into reliable operator-facing products.
European grid ecosystem
Methods are validated in collaboration with Alliander and TenneT, with a focus on practical grid-operation workflows.
Vision
Building the Intelligence Layer for Energy
Hypernode aims to become a trusted foundation-model platform for the energy ecosystem, enabling operators to plan, forecast, and operate increasingly complex grids with infrastructure-grade models and practical deployment paths.
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