| 02 Jun 2026
Experimental wind tunnel dataset of wake and turbine measurements for wind farm control
Abstract. Open-access experimental datasets play a central role in validating and benchmarking numerical models used in wind energy and wind-farm control research. However, publicly available datasets providing time-resolved turbine loads, actuator commands, and inflow characterisation under controlled operation remain scarce.
This paper presents a new open-access experimental dataset from wind-tunnel experiments featuring actuated, instrumented, scaled wind turbine models. The database includes time-resolved measurements of tower-base and rotating-shaft moments, rotor speed, generated torque and power, blade pitch angles, nacelle yaw angle, and controller commands. The inflow conditions are described in terms of wind speed, wind direction, air density, and wake-flow measurements, enabling detailed analyses of turbine response and controller behaviour under consistent, repeatable conditions.
The experiments cover a wide range of wake-control strategies, including yaw-based wake steering, curtailment and derating, Helix control, dynamic yaw actuation, Pulse wake mixing, individual pitch control, and several combinations of these strategies. The simultaneous availability of actuator commands, measured turbine response, and time-resolved structural loads enables detailed investigation of the controller performance, load variability, and dynamic turbine behaviour induced by active wake-control strategies.
In addition to the experimental measurements, the dataset is complemented by numerical models of the experiments, providing a reproducible experimental-numerical benchmarking framework that enables dataset extension, sensitivity analyses, and systematic validation of control-oriented aeroelastic and wake-interaction models.
The dataset is intended to support the validation and benchmarking of numerical tools for wind-farm control, the assessment of fatigue-relevant loading under wake-control operations, and to strengthen community efforts to improve transparency, reproducibility, and model fidelity in wind-farm design and control research.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Wind Energy Science.
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