PRACTICAL APPLICATIONS
Explore illustrative use cases, the data they need and how an operator could evaluate them.
Utilities and site operators
Data required: Metered demand, weather, calendar and operational context.
Evaluation: Forecast error, peak demand and baseline comparisons.
Forecasts remain uncertain; unusual events need explicit stress testing.
Grid and industrial asset teams
Data required: Condition monitoring, inspection and failure history.
Evaluation: Precision, missed failures and maintenance outcomes.
False alarms and missed faults require human review.
Renewable and storage operators
Data required: Generation forecasts, asset limits and dispatch constraints.
Evaluation: Curtailment, forecast accuracy and availability.
This site does not calculate dispatch or battery sizing.
Data centre developers and enterprise teams
Data required: IT load, utilisation, runtime, PUE and tariff assumptions.
Evaluation: Energy range, operating cost and sensitivity.
Annual averages do not represent peak capacity or reliability.
Industrial and commercial energy teams
Data required: Process schedules, load profiles and operating boundaries.
Evaluation: Shiftable load and operational impact.
Check process safety and customer obligations before control.
Engineering and procurement teams
Data required: Approved technical documents and controlled source libraries.
Evaluation: Source accuracy, retrieval relevance and review time.
Generated answers need traceable references and expert validation.
These are proposed applications, not deployed World Energy AI products. No live operational systems or AI models are connected.