Preprints
https://doi.org/10.5194/wes-2026-117
https://doi.org/10.5194/wes-2026-117
15 Jul 2026
 | 15 Jul 2026
Status: this preprint is currently under review for the journal WES.

Influence of environmental characteristics on power production in an offshore wind turbine in the Belgian North Sea

Rebeca Marini, Konstantinos Vratsinis, Pieter-Jan Daems, Timothy Verstraeten, Etienne Cheynet, and Jan Helsen

Abstract. Quantifying the influence of inflow atmospheric characteristics on wind turbine's operation is fundamental for performance assessment, operational diagnosis, and the estimation of power production. While it is well-established that wind speed is the primary driver of power output, additional environmental factors such as turbulence intensity, atmospheric stability, shear and veer are also known to influence the rotor captured inflow and the turbine's response. However, isolating and interpreting the contribution of each of these factors remain a continuing effort. This study presents a framework using operational data, as nacelle-mounted lidar, SCADA and environmental data, to analyse the impact of these factors in a single wind turbine in a wind farm on the Belgian offshore zone. A machine-learning model is trained to represent the power production deviation behaviour, and SHapley Additive exPlanations (SHAP) are applied to quantify the contribution of each environmental variable to predicted power output. Results show that, excluding wind speed, turbulence intensity and air density are the biggest predictors in the transition of torque-control to pitch-control of the wind turbine operation, with respective contributions that influence the power deviation prediction of 16.8 % and 14.5 %. As for higher wind speeds, air density appears as the main influential factors, contributing up to 32.8 % for the above-rated wind speed of the power curve.

Competing interests: At least one of the (co-)authors is a member of the editorial board of Wind Energy Science.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
Share
Rebeca Marini, Konstantinos Vratsinis, Pieter-Jan Daems, Timothy Verstraeten, Etienne Cheynet, and Jan Helsen

Status: open (until 12 Aug 2026)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Rebeca Marini, Konstantinos Vratsinis, Pieter-Jan Daems, Timothy Verstraeten, Etienne Cheynet, and Jan Helsen
Rebeca Marini, Konstantinos Vratsinis, Pieter-Jan Daems, Timothy Verstraeten, Etienne Cheynet, and Jan Helsen
Metrics will be available soon.
Latest update: 15 Jul 2026
Download
Short summary
We studied which environmental conditions affect the power produced by a single wind turbine without interference from nearby turbines. Using measured turbine and weather data together with machine learning, we found that the difference between air and sea temperature has a meaningful influence but is not included in commonly used power corrections. This could improve power predictions and wind resource assessments, and the method can be extended to larger groups of turbines.
Share
Altmetrics