Model Predictive Wind Turbine Control with Move-Blocking Strategy for Load Alleviation and Power Leveling

This contribution presents a Model Predictive Controller (MPC) with moveblocking strategy for combined power leveling and load alleviation in wind turbine operation with a focus on extreme loads. The controller is designed for a 3 MW wind turbine developed by W2E Wind to Energy GmbH and compared to...

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Bibliographic Details
Published in:Journal of physics. Conference series 2016-09, Vol.753 (5), p.52021
Main Authors: Jassmann, U, Dickler, S, Zierath, J, Hakenberg, M, Abel, D
Format: Article
Language:English
Subjects:
Control systems design
Leveling
Load alleviation
Multibody systems
Physics
Predictive control
Programmable logic controllers
Turbines
Wind turbines
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Summary:This contribution presents a Model Predictive Controller (MPC) with moveblocking strategy for combined power leveling and load alleviation in wind turbine operation with a focus on extreme loads. The controller is designed for a 3 MW wind turbine developed by W2E Wind to Energy GmbH and compared to a baseline controller, using a classic control scheme, which currently operates the wind turbine. All simulations are carried out with a detailed multibody simulation turbine model implemented in alaska Wind. The performance of the two different controllers is compared using a 50-year Extreme Operation Gust event, since it is one of the main design drivers for the wind turbine considered in this work. The implemented MPC is able to level electrical output power and reduce mechanical loads at the same time. Without de-rating the achieved control results, a move-blocking strategy is utilized and allowed to reduce the computational burden of the MPC by more than 50% compared to a baseline MPC implementation. This even allows to run the MPC on a state of the art Programmable Logic Controller.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/753/5/052021