Schaeffler Optimizes Wind Turbines Using Closed Loop
System optimization through advanced simulation programs Optimized bearing design is fundamental to maximizing wind turbine reliability and cost-effectiveness in operation. Hence,
Fig. 1. The closed-loop model-based wind farm control framework. A simplified surrogate model of the wind farm is used to represent the flow and turbine behavior at a low computational cost. The first step in the controller is model adaptation, implying the estimation of the inputs relevant for the current wind farm situation.
This closed-loop and model-based control solution was tested in a high-fidelity simulation subjected to a time-varying inflow, being the first of its kind in the literature. The wind direction and wind speed in the simulation contain strong changes to stress-test the controller.
Secondly, the setpoint optimization leverages the adapted surrogate model to find the turbine control setpoints that maximize a certain objective. In this work, the objective is power maximization and the control variables are the turbine yaw angles. Fig. 1. The closed-loop model-based wind farm control framework.
The surrogate model of Section 3 is used to design a closed-loop wind farm controller. The wind farm studied in this article is a virtual offshore wind farm with six DTU 10 MW turbines spaced at 5 D × 3 D as shown in Fig. 6. The model adaptation algorithm is described in Section 4.1.
System optimization through advanced simulation programs Optimized bearing design is fundamental to maximizing wind turbine reliability and cost-effectiveness in operation. Hence,
Furthermore, Ciri et al. [21] presents a closed-loop and model-free control algorithm that improves the performance of turbines inside a wind farm, demonstrated in high-fidelity simulations
With the closed-loop engineering approach, Schaeffler, as a development partner in the wind industry, goes far beyond providing bearing solutions for onshore and offshore wind turbines: In
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