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

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 perturbati...

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Main Authors: Timothé Jard, Reda Snaiki
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Wind
Subjects:
Online Access:https://www.mdpi.com/2674-032X/3/2/9
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author Timothé Jard
Reda Snaiki
author_facet Timothé Jard
Reda Snaiki
author_sort Timothé Jard
collection DOAJ
description 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.
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spelling doaj.art-cdf5181531014e33be60ef2c699311212023-11-18T13:06:40ZengMDPI AGWind2674-032X2023-03-013213115010.3390/wind3020009Real-Time Repositioning of Floating Wind Turbines Using Model Predictive Control for Position and Power RegulationTimothé Jard0Reda Snaiki1Department of Mechanical Engineering, École de Technologie Supérieure, Université du Québec, Montréal, QC H3C 1K3, CanadaDepartment of Mechanical Engineering, École de Technologie Supérieure, Université du Québec, Montréal, QC H3C 1K3, CanadaAs 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.https://www.mdpi.com/2674-032X/3/2/9offshore wind energyfloating wind turbineposition controlpower regulationmodel predictive control
spellingShingle Timothé Jard
Reda Snaiki
Real-Time Repositioning of Floating Wind Turbines Using Model Predictive Control for Position and Power Regulation
Wind
offshore wind energy
floating wind turbine
position control
power regulation
model predictive control
title Real-Time Repositioning of Floating Wind Turbines Using Model Predictive Control for Position and Power Regulation
title_full Real-Time Repositioning of Floating Wind Turbines Using Model Predictive Control for Position and Power Regulation
title_fullStr Real-Time Repositioning of Floating Wind Turbines Using Model Predictive Control for Position and Power Regulation
title_full_unstemmed Real-Time Repositioning of Floating Wind Turbines Using Model Predictive Control for Position and Power Regulation
title_short Real-Time Repositioning of Floating Wind Turbines Using Model Predictive Control for Position and Power Regulation
title_sort real time repositioning of floating wind turbines using model predictive control for position and power regulation
topic offshore wind energy
floating wind turbine
position control
power regulation
model predictive control
url https://www.mdpi.com/2674-032X/3/2/9
work_keys_str_mv AT timothejard realtimerepositioningoffloatingwindturbinesusingmodelpredictivecontrolforpositionandpowerregulation
AT redasnaiki realtimerepositioningoffloatingwindturbinesusingmodelpredictivecontrolforpositionandpowerregulation