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    Hybrid Model Predictive Control of Floating Offshore Wind Turbines With Artificial Muscle Actuated Mooring Lines

    Source: Journal of Dynamic Systems, Measurement, and Control:;2022:;volume( 144 ):;issue: 005::page 51003-1
    Author:
    Wu, Zhongyou
    ,
    Li, Yaoyu
    DOI: 10.1115/1.4053429
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Floating offshore wind turbines (FOWTs) are subject to undesirable platform motion and a significant increases in fatigue loads compared to their onshore counterparts. We have recently proposed using the fishing line artificial muscle (FLAM) actuators to realize active mooring line force control (AMLFC) for platform stabilization and thus load reduction, which features a compact design and no need for turbine redesign. However, as for the thermally activated FLAM actuators, a major control challenge lies in the asymmetric dynamics for the heating and the cooling half cycle of operation. In this paper, for a tension-leg platform (TLP) based FOWT with FLAM actuator based AMLFC, a hybrid dynamic model is obtained with platform pitch and roll degrees-of-freedom included. Then a hybrid model predictive control (HMPC) strategy is proposed for platform motion stabilization, with preview information on incoming wind and wave. A move blocking scheme is used to achieve reasonable computational efficiency. Fatigue, aerodynamics, structures, and turbulence (FAST) based simulation study is performed using the National Renewable Energy Laboratory (NREL) 5 MW wind turbine model. Under different combinations of wind speed, wave height and wind directions, simulation results show that the proposed control strategy can significantly reduce the platform roll and tower-base side-to-side bending moment, with a mild level of actuator power consumption.
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      Hybrid Model Predictive Control of Floating Offshore Wind Turbines With Artificial Muscle Actuated Mooring Lines

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4284698
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    contributor authorWu, Zhongyou
    contributor authorLi, Yaoyu
    date accessioned2022-05-08T09:04:21Z
    date available2022-05-08T09:04:21Z
    date copyright2/7/2022 12:00:00 AM
    date issued2022
    identifier issn0022-0434
    identifier otherds_144_05_051003.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4284698
    description abstractFloating offshore wind turbines (FOWTs) are subject to undesirable platform motion and a significant increases in fatigue loads compared to their onshore counterparts. We have recently proposed using the fishing line artificial muscle (FLAM) actuators to realize active mooring line force control (AMLFC) for platform stabilization and thus load reduction, which features a compact design and no need for turbine redesign. However, as for the thermally activated FLAM actuators, a major control challenge lies in the asymmetric dynamics for the heating and the cooling half cycle of operation. In this paper, for a tension-leg platform (TLP) based FOWT with FLAM actuator based AMLFC, a hybrid dynamic model is obtained with platform pitch and roll degrees-of-freedom included. Then a hybrid model predictive control (HMPC) strategy is proposed for platform motion stabilization, with preview information on incoming wind and wave. A move blocking scheme is used to achieve reasonable computational efficiency. Fatigue, aerodynamics, structures, and turbulence (FAST) based simulation study is performed using the National Renewable Energy Laboratory (NREL) 5 MW wind turbine model. Under different combinations of wind speed, wave height and wind directions, simulation results show that the proposed control strategy can significantly reduce the platform roll and tower-base side-to-side bending moment, with a mild level of actuator power consumption.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleHybrid Model Predictive Control of Floating Offshore Wind Turbines With Artificial Muscle Actuated Mooring Lines
    typeJournal Paper
    journal volume144
    journal issue5
    journal titleJournal of Dynamic Systems, Measurement, and Control
    identifier doi10.1115/1.4053429
    journal fristpage51003-1
    journal lastpage51003-12
    page12
    treeJournal of Dynamic Systems, Measurement, and Control:;2022:;volume( 144 ):;issue: 005
    contenttypeFulltext
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