Ensemble-Based Flow Field Estimation Using the Dynamic Wind Farm Model FLORIDyn

Marcus Becker (), Dries Allaerts and Jan-Willem van Wingerden ()
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Marcus Becker: Delft Center for Systems and Control, TU Delft, Mekelweg 2, 2628 CD Delft, The Netherlands
Dries Allaerts: Faculty of Aerospace Engineering, TU Delft, Kluyverweg 1, 2629 HS Delft, The Netherlands
Jan-Willem van Wingerden: Delft Center for Systems and Control, TU Delft, Mekelweg 2, 2628 CD Delft, The Netherlands

Energies, 2022, vol. 15, issue 22, 1-23

Abstract: Wind farm control methods allow for a more flexible use of wind power plants over the baseline operation. They can be used to increase the power generated, to track a reference power signal or to reduce structural loads on a farm-wide level. Model-based control strategies have the advantage that prior knowledge can be included, for instance by simulating the current flow field state into the near future to take adequate control actions. This state needs to describe the real system as accurately as possible. This paper discusses what state estimation methods are suitable for wind farm flow field estimation and how they can be applied to the dynamic engineering model FLORIDyn. In particular, we derive an Ensemble Kalman Filter framework which can identify heterogeneous and changing wind speeds and wind directions across a wind farm. It does so based on the power generated by the turbines and wind direction measurements at the turbine locations. Next to the states, this framework quantifies uncertainty for the resulting state estimates. We also highlight challenges that arise when ensemble methods are applied to particle-based flow field simulations. The development of a flow field estimation framework for dynamic low-fidelity wind farm models is an essential step toward real-time dynamic model-based closed-loop wind farm control.

Keywords: wind field estimation; dynamic wind farm modelling; wind farm control; ensemble Kalman filter (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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