Optimum seeking-based non-linear controller to maximise energy capture in a variable speed wind turbine

Abstract

Abstract:In this study, an optimum seeking-based robust non-linear controller is proposed to maximise wind energy captured by variable speed wind turbines at low-to-medium wind speeds. The proposed strategy simultaneously controls the blade pitch angle and tip-speed ratio, through the turbine rotor angular speed, to an optimal point at which the power coefficient, and hence the wind turbine efficiency, is maximum. The optimal points are given to the controller by an optimisation algorithm that seeks the unknown optimal blade pitch angle and rotor speed. The control method allows for aerodynamic rotor power maximisation without exact knowledge of the wind turbine model. A representative numerical simulation is presented to show that the wind turbine can be accurately controlled to achieve maximum energy capture.

Pitch angle control of wind turbine systems in cold weather conditions using $$\mu$$ μ robust controller

“…Variation of produced power and load serve as proofs for such dysfunctionality. Ice masses on the turbine change the natural frequency of the turbine's components and also the behavior of the system's dynamic [14][15][16]. The control system has also been affected by these conditions.…”

“…The adjustment of the variable pitch angle and the variable rotor speed, respectively, results in the maximization of the electrical power and minimization of the turbine's dynamic load. It is note worthy that the adjustment of the variable rotor speed not only minimizes the turbine's dynamic load, but also increases the system's lifetime [15,16]. The objective of designing the controller is to maximize the electrical power production at low wind speed and to maintain it at high wind speed.…”

Wind Velocity Sensorless Maximum Power Point Tracking Algorithm in Grid-connected Wind Energy Conversion System

“…The non-linear based MPPT methods in [7][8][9] and slidingmode-based MPPT [10] are more efficient during disturbances in a WECS, but these methods need system modeling, as in [2]. A neural network-based method proposed in [11] needed on-line training to track the optimum points.…”

“…It does not require any prior knowledge about the turbine, generator, and wind characteristics and addresses the issues related to neediness of the modeling parameters in [2,[7][8][9]. Also, [19] is suitable with variable pitch angle as well.…”

A Maximum Power Tracking Technique for Grid-Connected DFIG-Based Wind Turbines

“…The mechanical subsystem consists of the blade aerodynamics and the drivetrain dynamics. The mechanical subsystem is modeled using the FAST (Fatigue, Aerodynamics, Structures, and Turbulence) simulator, which has been developed by the National Renewal Energy Laboratory (NREL) [18], which has been used as the analysis tool to examine the validity of the control schemes applied to wind turbines in the literature [10], [13], [14].…”