# Wind Turbine SCADA Data For Early Fault Detection

## About the Dataset

This dataset, originally published as "CARE to Compare: Wind Turbine Anomaly Detection Dataset," contains real-world SCADA data from wind turbines. It is designed for testing and developing anomaly detection algorithms for wind energy systems.

### Dataset Overview
- **Duration:** 89 years of cumulative operating data
- **Turbines:** 36 wind turbines across 3 wind farms
- **Datasets:** 95 total datasets
  - 44 contain labeled anomaly events
  - 51 represent normal behavior
- **Resolution:** 10-minute SCADA data intervals
- **Feature Count:**
  - Wind Farm A: 86 features
  - Wind Farm B: 257 features
  - Wind Farm C: 957 features
- **Data Structure:** Each dataset contains 1 year of training data plus 4-98 days of prediction data

### Key Features
- **Detailed fault information**: Most comprehensive publicly available wind turbine fault dataset
- **Status-based labels**: Ensures high-quality training data
- **Labeled anomaly events**: 44 labeled time frames of faults
- **Normal operation datasets**: 51 time series with no faults
- **Comprehensive sensor descriptions**: Includes units and descriptions for all measured variables

## Potential Applications
- **Anomaly detection algorithm development and testing**
- **Predictive maintenance modeling**
- **Wind turbine performance analysis**
- **SCADA-based condition monitoring**
- **Benchmark testing using the CARE score (Coverage, Accuracy, Reliability, and Earliness)**

## Citation
If you use this dataset, please cite the original paper:

> Güuck, C., Roelofs, C.M.A., & Faulstich, S. (2024). CARE to Compare: A real-world dataset for anomaly detection in wind turbine data. arXiv:2404.10320

## Original Source
This dataset was originally published at:
- [Zenodo](https://zenodo.org/doi/10.5281/zenodo.10958774)
- [Fordatis](http://dx.doi.org/10.24406/fordatis/343)

## Modification Note
The only modification made to the original dataset is the replacement of semicolons with commas as CSV separators to facilitate easier data loading and analysis.

## License
This dataset is shared under the **Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)** license.