Real-Time Repositioning of Floating Wind Turbines Using Model Predictive Control for Position and Power Regulation

Author:

Jard Timothé1,Snaiki Reda1ORCID

Affiliation:

1. Department of Mechanical Engineering, École de Technologie Supérieure, Université du Québec, Montréal, QC H3C 1K3, Canada

Abstract

As offshore wind capacity could grow substantially in the coming years, floating offshore wind turbines (FOWTs) are particularly expected to make a significant contribution to the anticipated global installed capacity. However, FOWTs are prone to several issues due partly to environmental perturbations and their system configuration which affect their performances and jeopardize their structural integrity. Therefore, advanced control mechanisms are required to ensure good performance and operation of FOWTs. In this study, a model predictive control (MPC) is proposed to regulate FOWTs’ power, reposition their platforms to reach predefined target positions and ensure their structural stability. An efficient nonlinear state space model is used as the internal MPC predictive model. The control strategy is based on the direct manipulation of the thrust force using three control inputs, namely the yaw angle, the collective blade pitch angle, and the generator torque without the necessity of additional actuators. The proposed controller accounts for the environmental perturbations and satisfies the system constraints to ensure good performance and operation of the FOWTs. A realistic scenario for a 5-MW reference wind turbine, modeled using OpenFAST and Simulink, has been provided to demonstrate the robustness of the proposed MPC controller. Furthermore, the comparison of the MPC model and a proportional-integral-derivative (PID) model to satisfy the three predefined objectives indicates the superior performances of the MPC controller.

Funder

Natural Sciences and Engineering Research Council

Publisher

MDPI AG

Reference47 articles.

1. Musial, W., Beiter, P., Spitsen, P., Nunemaker, J., Gevorgian, V., Cooperman, A., Hammond, R., and Shields, M. (2020). 2019 Offshore Wind Technology Data Update, National Renewable Energy Laboratory (NREL). NREL/TP-5000-77411.

2. GWEC (2021). Global Wind Report 2021, Global Wind Energy Council. Available online: https://gwec.net/global-wind-report-2021/.

3. Jonkman, J.M. (2007). Dynamics Modeling and Loads Analysis of an Offshore Floating Wind Turbine. [Ph.D. Thesis, National Renewable Energy Laboratory]. NREL/TP-500-41958.

4. Swart, R., Coppens, C., Gordjin, H., Piek, M., Ruyssenaars, P., Schrander, J.J., Hoogwijk, M., Papalexandrou, M., and Horalek, J. (2009). Europe’s Onshore Andoffshore Wind Energy Potential: An Assessment of Environmental and Economic Constraints. (No. 6/2009), European Environment Agency.

5. A Synthesis of Feasible Control Methods for Floating Offshore Wind Turbine System Dynamics;Shah;Renew. Sustain. Energy Rev.,2021

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