Gain-scheduling control of a floating offshore wind turbine above rated wind speed

Bagherieh, Omid; Nagamune, Ryozo

doi:10.1007/s11768-015-4152-0

Cited by 48 publications

(29 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Great reductions in the platform-pitch motion and in the mechanical component loads were achieved. However, the generator speed regulation quickness was degraded.Several Linear Quadratic Regulator (LQR) based controller designs are compared with the baseline blade-pitch PI controller in [12]. The LQR Gain-Scheduling (GS) and the Linear Parameter-Varying (LPV) GS State-Feedback (SF) control techniques show the best results.…”

mentioning

confidence: 99%

See 1 more Smart Citation

An Advanced Control Technique for Floating Offshore Wind Turbines Based on More Compact Barge Platforms

Olondriz¹,

Elorza²,

Jugo

et al. 2018

Energies

View full text Add to dashboard Cite

Hydrodynamic Floating Offshore Wind Turbine (FOWT) platform specifications are typically dominated by seaworthiness and maximum operating platform-pitch angle-related requirements. However, such specifications directly impact the challenge posed by an FOWT in terms of control design. The conventional FOWT systems are typically based on large, heavy floating platforms, which are less likely to suffer from the negative damping effect caused by the excessive coupling between blade-pitch control and platform-pitch motion. An advanced control technique is presented here to increase system stability for barge type platforms. Such a technique mitigates platform-pitch motions and improves the generator speed regulation, while maintaining blade-pitch activity and reducing blade and tower loads. The NREL's 5MW + ITI Energy barge reference model is taken as a basis for this work. Furthermore, the capabilities of the proposed controller for performing with a more compact and less hydrodynamically stable barge platform is analysed, with encouraging results.Several attempts have been done to control and improve FOWT systems-however, not so many for barge mounted systems. This is because of the dilemma presented by this type of platform. When the blade-pitch action tries to regulate the generator speed in the above rated wind speed, a coupling between blade-pitch and platform-pitch motions can happen [10], known as the negative platform damping effect. This phenomenon makes the turbine unstable, potentially damaging mechanical components. One of the first and most complete studies done to tackle this phenomenon was carried out in [11], where three control alternatives were proposed to mitigate the barge platform-pitch motions. The best results were achieved detuning the blade-pitch PI control gains. Great reductions in the platform-pitch motion and in the mechanical component loads were achieved. However, the generator speed regulation quickness was degraded.Several Linear Quadratic Regulator (LQR) based controller designs are compared with the baseline blade-pitch PI controller in [12]. The LQR Gain-Scheduling (GS) and the Linear Parameter-Varying (LPV) GS State-Feedback (SF) control techniques show the best results. The LQR GS control provides the best power regulation, whereas the LPV GS SF provides the best platform-pitch damping. The baseline blade-pitch PI controller used for the comparison is tuned with those blade-pitch PI gains used for onshore wind turbines. Unfortunately, a mechanical load analysis is missing to verify the impact of the proposed controllers on the mechanical components.A comparison between the Individual Pitch Control (IPC) and the Collective Pitch Control (CPC) is presented in [13]. The IPC is based on three modules: the Disturbance Accommodating Control (DAC) aimed at eliminating the wind disturbances, the Model Predictive Control (MPC) to remove the influence of wave disturbances, and the fuzzy control module to combine both these algorithms. Both IPC and CPC techniques improve the power productio...

show abstract

mentioning

confidence: 99%

“…Several Linear Quadratic Regulator (LQR) based controller designs are compared with the baseline blade-pitch PI controller in [12]. The LQR Gain-Scheduling (GS) and the Linear Parameter-Varying (LPV) GS State-Feedback (SF) control techniques show the best results.…”

mentioning

confidence: 99%

An Advanced Control Technique for Floating Offshore Wind Turbines Based on More Compact Barge Platforms

Olondriz¹,

Elorza²,

Jugo

et al. 2018

Energies

View full text Add to dashboard Cite

show abstract

“…For this, the PI is reinforced by a control process called gain scheduling (GS). As underlined in [2,20], the principle is based on the linearization of the system at operating points in order to get as close as possible to the nonlinear behavior of the system.…”

Section: Collective Pitch Controlmentioning

confidence: 99%

Control Strategies for Floating Offshore Wind Turbine: Challenges and Trends

et al. 2019

View full text Add to dashboard Cite

The offshore wind resource has huge energy potential. However, wind turbine floating structures have to withstand harsh conditions. Strong wind and wave effects combine to generate vibrations, fatigue, and heavy loads on the structure and other elements of the wind turbine. These structural problems increase maintenance requirements and risk of failure, while reducing availability and energy production. Another challenge for wind energy is to reduce production costs in order to be competitive with other alternatives. From the control point of view, the objective of lowering costs can be achieved by operating the turbine close to its optimum point of operation under partial load, guaranteeing reliability by reducing structural loads and regulating the power generated in strong wind regimes. In this typical and challenging context, this paper proposes a critical state-of-the-art review, discussing challenges and trends on floating offshore wind turbines control.

show abstract

“…First, we can rewrite the observer (19) as follows: Then, we can derive the system equation of sliding mode estimation state. First, we can rewrite the observer state Eq.…”

Section: The Descriptor Error and Estimation State Dynamicsmentioning

confidence: 99%

Active Fault-Tolerant Control for Wind Turbine with Simultaneous Actuator and Sensor Faults

et al. 2017

View full text Add to dashboard Cite

The purpose of this paper is to show a novel fault-tolerant tracking control (FTC) strategy with robust fault estimation and compensating for simultaneous actuator sensor faults. Based on the framework of fault-tolerant control, developing an FTC design method for wind turbines is a challenge and, thus, they can tolerate simultaneous pitch actuator and pitch sensor faults having bounded first time derivatives. The paper’s key contribution is proposing a descriptor sliding mode method, in which for establishing a novel augmented descriptor system, with which we can estimate the state of system and reconstruct fault by designing descriptor sliding mode observer, the paper introduces an auxiliary descriptor state vector composed by a system state vector, actuator fault vector, and sensor fault vector. By the optimized method of LMI, the conditions for stability that estimated error dynamics are set up to promote the determination of the parameters designed. With this estimation, and designing a fault-tolerant controller, the system’s stability can be maintained. The effectiveness of the design strategy is verified by implementing the controller in the National Renewable Energy Laboratory’s 5-MW nonlinear, high-fidelity wind turbine model (FAST) and simulating it in MATLAB/Simulink.

show abstract

Gain-scheduling control of a floating offshore wind turbine above rated wind speed

Cited by 48 publications

References 15 publications

An Advanced Control Technique for Floating Offshore Wind Turbines Based on More Compact Barge Platforms

An Advanced Control Technique for Floating Offshore Wind Turbines Based on More Compact Barge Platforms

Control Strategies for Floating Offshore Wind Turbine: Challenges and Trends

Active Fault-Tolerant Control for Wind Turbine with Simultaneous Actuator and Sensor Faults

Contact Info

Product

Resources

About