Agents and machine learning for power systems.
Conventional power system studies explore only a fraction of what could happen. We use machine learning and physics-based modeling to explore more combinations of load generation and outages, showing where a system is at risk and where it can do more with existing infrastructure.
Power planning and reliability
Plan generation, storage and dispatch to meet growing compute demand. Test capacity, cost and reliability across operating scenarios.
Automate electrical studies
Compare electrical designs, generation and storage options. Automate studies across your existing engineering tools.
Rack-to-facility power optimization
Translate rack power profiles into facility deployment limits. Test power smoothing and allocation strategies to support more compute within existing power budgets.
Congestion forecasting and market risk
Model how changes in load, generation and the network affect congestion, nodal prices and portfolio exposure.
