Description of the SCADA dataset of an onshore La Houte Bourne wind farm in Villeneuve-d’Ascq, France

1. Dataset Overview
This dataset contains Supervisory Control and Data Acquisition (SCADA) measurements collected from an onshore wind farm located in Villeneuve-d’Ascq, France, over eight years (from 1 January 2013 to 31 December 2020). The wind farm has four wind turbines of the MM82 model, manufactured by Senvion. Those wind turbines are labeled as R80736, R80721, R80711, and R80790. The rated power of each turbine is 2 MW. Each wind turbine at the wind farm has a nominal power of 2050 kW, a cut-in wind speed of 4 m/s, and a cut-out wind speed of 22 m/s. The blade length and hub height are 40 m and 80 m, respectively.

There were 34 process parameters measured at an interval of 10 min for each wind turbine (WT), and in total 1,057,868 samples were recorded. The dataset includes many parameters, such as wind speed, absolute wind direction, outdoor temperature, rotor bearing temperature, gearbox bearing temperature, generator bearing temperature, gearbox oil sump temperature, generator speed, generated power, torque, grid voltage, grid frequency, vane position, pitch angle, and more. For each parameter, the average value, standard deviation, maximum, and minimum values were collected at every interval.

During the period from 1 January 2013 to 31 December 2016, the gearbox bearing temperature of the R80721 wind turbine reached a maximum value of 84.12°C at the data sample 70,995. This unusually high temperature indicates a failure of the gearbox bearing associated with the high-speed shaft, which was recorded on 2 January 2015 at 08:50.

The data include operational measurements recorded from wind turbines and can be used for research in wind turbine performance analysis, condition monitoring, and fault detection methods.
The SCADA dataset for the La Haute Borne Wind Farm was previously available at the link: https://www.engie.com/en/activities/renewable-energies/wind-energy. However, the dataset is currently not accessible.
Data set format: CSV (semicolon-separated values)
The SCADA system records turbine operational parameters continuously and stores aggregated measurements for monitoring and performance analysis.
2. Related published papers:
i. Dao, P. B., Barszcz, T., & Staszewski, W. J. (2024). Anomaly detection of wind turbines based on stationarity analysis of SCADA data. Renewable Energy, 232. https://doi.org/10.1016/j.renene.2024.121076
ii. Dao, P. B. (2022). On Wilcoxon rank sum test for condition monitoring and fault detection of wind turbines. Applied Energy, 318. https://doi.org/10.1016/j.apenergy.2022.119209
iii. Dao, P. B. (2023). On Cointegration Analysis for Condition Monitoring and Fault Detection of Wind Turbines Using SCADA Data. Energies, 16(5). https://doi.org/10.3390/en16052352
iv. Knes, P., & Dao, P. B. (2024). Machine Learning and Cointegration for Wind Turbine Monitoring and Fault Detection: From a Comparative Study to a Combined Approach. Energies, 17(20), 5055. https://doi.org/10.3390/en17205055