Tidal stream turbine control: An active disturbance rejection control approach

Zhou, Zhibin; Elghali, Seifeddine Ben; Benbouzid, Mohamed; Amirat, Yassine; Elbouchikhi, Elhoussin; Feld, Gilles

doi:10.1016/j.oceaneng.2020.107190

Cited by 36 publications

(35 citation statements)

References 29 publications

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“…The PMSM and EV numerical parameters are presented in Tables 1 and 2. For comparison purposes, the following fitness functions are defined to study the regulators performance [43]: 2 .dt (33) I AE = |e(t)| .dt (34)…”

Section: Simulation Resultsmentioning

confidence: 99%

ADRC-Based Robust and Resilient Control of a 5-Phase PMSM Driven Electric Vehicle

et al. 2020

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The selection of electric machines for an Electric Vehicle (EV) is mainly based on reliability, efficiency, and robustness, which makes the 5-phase Permanent Magnet Synchronous Motor (PMSM) among the best candidates. However, control performance of any motor drive can be deeply affected by both: (1) internal disturbances caused by parametric variations and model uncertainties and (2) external disturbances related to sensor faults or unexpected speed or torque variation. To ensure stability under those conditions, an Active Disturbance Rejection Controller (ADRC) based on an online dynamic compensation of estimated internal and external disturbances, and a Linear ADRC (LADRC) are investigated in this paper. The control performance was compared with traditional controller and evaluated by considering parametric variation, unmodeled disturbances, and speed sensor fault. The achieved results clearly highlight the effectiveness and high control performance of the proposed ADRC-based strategies.

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Section: Simulation Resultsmentioning

confidence: 99%

ADRC-Based Robust and Resilient Control of a 5-Phase PMSM Driven Electric Vehicle

et al. 2020

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“…The tidal power captured by the turbine and the corresponding torque is expressed as below [9]: Where, β denotes the pitch angle, v t is the tidal speed, ρ represents water density, λ denotes the tip-speed ratio, C p represents the power coefficient, A denotes the swept area of the blades, R denotes the radius of the blades, and ω m represents the speed of the rotor.…”

Section: Tidal Power Modelmentioning

confidence: 99%

“…The proposed strategy will be compared to the second-order sliding mode control (SMC) [9], and the conventional (PI) controller methods [19]. Two scenarios are considered.…”

Section: Numerical and Experimental Validationmentioning

confidence: 99%

“…The authors proposed an association of the tidal system with the superconducting magnetic energy system (SCMES), for which the jaya-based controller is applied; however, this association improves the costs and maintenance time only. A novel active disturbance rejection controller as an alternative to the conventional Proportional Integral (PI) control is proposed in [9]. This strategy treats the parameter uncertainties or changes as an element to be rejected which can be canceled during the control design.…”

Section: Introductionmentioning

confidence: 99%

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Energy-Based Combined Nonlinear Observer and Voltage Controller for a PMSG Using Fuzzy Supervisor High Order Sliding Mode in a Marine Current Power System

et al. 2021

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A permanent magnet synchronous generator (PMSG) in s grid-connected tidal energy conversion system presents numerous advantages such as high-power density and ease of maintenance. However, the nonlinear properties of the generator and parametric uncertainties make the controller design more than a simple challenge. Within this paper we present a new combined passivity-based voltage control (PBVC) with a nonlinear observer. The PBVC is used to design the desired dynamics of the system, while the nonlinear observer serves to reconstruct the measured signals. A high order sliding-mode based fuzzy supervisory approach is selected to design the desired dynamics. This paper addresses the following two main parts: controlling the PMSG to guarantee the maximum tidal power extraction and integrate into to the grid-side converter (GSC), for this the new controller is proposed. The second task is to regulate the generated reactive power and the DC-link voltage to their references under any disturbances related to the machine-side converter (MSC). Furthermore, the robustness of the controller against parameter changes was taken into consideration. The developed controller is tested under parameter variations and compared to benchmark nonlinear control methods. Numerical simulations are performed in MATLAB/Simulink which clearly demonstrates the robustness of the proposed technique over the compared control methods. Moreover, the proposed controller is also validated using a processor in the loop (PIL) experiment using Texas Instruments (TI) Launchpad.

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“…For the control scheme of the generator side of a tidal turbine system, Zhou et al [3] proposed an Active Disturbance Rejection Control (ADRC) approach to replace the conventional PI controllers.…”

Section: Introductionmentioning

confidence: 99%

Dynamic, Fully Coupled, Electro-mechanical Models of Tidal Turbines

Ortega¹,

Tomy²,

Shek³

et al. 2020

Preprint

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Production of electricity using hydro-kinetic tidal turbines has many challenges that must to be overcome to ensure reliable, economic and practical solutions. Energy from flowing water is converted by a system comprising: the turbine rotor blades, a gearbox, an electrical generator, control systems, power electronics, export cables, and a connection to the electricity grid. To date these have often been modelled using simulations of independent systems, lacking bi-directional, real-time, coupling. This approach leads to critical effects being missed. Turbulence in the flow, results in large velocity fluctuations around the blades, causing rapid variation in the shaft torque and generator speed, and consequently in the voltage seen by the power electronics and consequently the export power quality. The resulting poor quality power may be unacceptable to the grid. Conversely, grid frequency and voltage changes can also cause the generator speed to change, resulting in changes to the shaft speed and torque and consequently changes to the lift and drag forces acting on the blades. Clearly, fully integrated, bi-directional, models are needed. Here we present two fully coupled models which use different approaches to model the hydrodynamics of rotor blades. The first model uses Blade Element Momentum Theory (BEMT), resulting in an efficient tool for turbine designers. The second model also uses BEMT combines this with an actuator line model of the blades coupled to an unsteady computational fluid dynamics (CFD) simulation. This simulation, implemented in OpenFOAM, uses an energy balance to compute the shaft speed. Both the BEMT and CFD models are coupled to an Open Modellica model of the electro-mechanical system. Both models have been used to simulate the performance of a 1.2m diameter, scale model, of a three bladed horizontal axis tidal turbine tested in the University of Edinburgh FloWave Ocean Energy Research Facility. The turbulent flow around the blades and the mechanical-electrical variables during the stable period of operation are analysed. Time series and tabulated average values of mechanical thrust, power, torque, and rotational speed as well as electrical variables of generator power, electromagnetic torque, voltage and current are presented for the coupled system simulation. The relationship between the mechanical and electrical variables and the results from both tidal turbine approaches are discussed. Our comparison shows that while the BEMT model provides an effective design tool (leading to slightly more conservative designs), the CFD/BEMT simulations provide more accurate predictions of the blade loads which can be especially important in assessing fatigue on the blades (though at an increased computational cost).

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Tidal stream turbine control: An active disturbance rejection control approach

Cited by 36 publications

References 29 publications

ADRC-Based Robust and Resilient Control of a 5-Phase PMSM Driven Electric Vehicle

ADRC-Based Robust and Resilient Control of a 5-Phase PMSM Driven Electric Vehicle

Energy-Based Combined Nonlinear Observer and Voltage Controller for a PMSG Using Fuzzy Supervisor High Order Sliding Mode in a Marine Current Power System

Dynamic, Fully Coupled, Electro-mechanical Models of Tidal Turbines

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