An Economic Model Predictive Control Approach for Load Mitigation on Multiple Tower Locations of Wind Turbines

An Economic Model Predictive Control Approach for Load Mitigation on Multiple Tower Locations of Wind Turbines

Feng, Z. (TU Delft Team Riccardo Ferrari)
Gallo, A.J. (TU Delft Team Riccardo Ferrari)
Liu, Y. (TU Delft Team Riccardo Ferrari)
Pamososuryo, A.K. (TU Delft Team Jan-Willem van Wingerden)
Ferrari, Riccardo M.G. (TU Delft Team Riccardo Ferrari)
van Wingerden, J.W. (TU Delft Team Jan-Willem van Wingerden)

2022

The current trend in the evolution of wind turbines is to increase their rotor size in order to capture more power. This leads to taller, slender and more flexible towers, which thus experience higher dynamical loads due to the turbine rotation and environmental factors. It is hence compelling to deploy advanced control methods that can dynamically counteract such loads, especially at tower positions that are more prone to develop cracks or corrosion damages. Still, to the best of the authors’ knowledge, little to no attention has been paid in the literature to load mitigation at multiple tower locations. Furthermore, there is a need for control schemes that can balance load reduction with optimization of power production. In this paper, we develop an Economic Model Predictive Control (eMPC) framework to address such needs. First, we develop a linear modal model to account for the tower flexural dynamics. Then we incorporate it into an eMPC framework, where the dynamics of the turbine rotation are expressed in energy terms. This allows us to obtain a convex formulation, that is computationally attractive. Our control law is designed to avoid the "turn-pike" behavior and guarantee recursive feasibility. We demonstrate the performance of the proposed controller on a 5MW reference WT model: the results illustrate that the proposed controller is able to reduce the tower loads at multiple locations, without significant effects to the generated power.

Economics
Vibrations
Damping
Computational modeling
Poles and towers
Fatique
Wind turbines

http://resolver.tudelft.nl/uuid:955e1492-4f5a-4782-8042-cf0961ae9289

https://doi.org/10.1109/CDC51059.2022.9992553

IEEE

2023-07-10

978-1-6654-6761-2

Proceedings of the IEEE 61st Conference on Decision and Control (CDC 2022)

IEEE 61st Conference on Decision and Control (CDC 2022), 2022-12-06 → 2022-12-09, Cancún, Mexico

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

conference paper

© 2022 Z. Feng, A.J. Gallo, Y. Liu, A.K. Pamososuryo, Riccardo M.G. Ferrari, J.W. van Wingerden