Wind AI Bench: Wind Energy Datasets for AI/ML Benchmarking

National Laboratory of the Rockies provides a data lake containing multiple datasets for wind energy research. The data includes wind plant power production for various layouts, flow around turbine airfoils, and turbine noise production. Its purpose is to establish a standard benchmark for testing, comparing, and deploying new AI/ML methods.

Use Cases

• Benchmark AI models for wind plant power production prediction based on layout and wind flow scenarios.
• Train machine learning models for aerodynamic flow simulation around wind turbine blades.
• Develop predictive models for wind turbine noise production.
• Compare new AI/ML methods against established benchmarks for wind energy problems.

Strengths

• Data is provided with metadata detailing generation and formatting for each dataset.
• Includes example notebooks and documentation showing how to access the data for ML modeling.
• Released under a permissive CC-BY-4.0 license.

Limitations

• Row count and total dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

National Laboratory of the Rockies

Collection Method

Data lake containing multiple generated datasets for fundamental wind energy problems.

Time Range

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Freshness

Last updated date is unknown.

Geography

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