Control Of Variable Speed Wind Turbine Research Articles

Recurrent neural network for pitch control of variable-speed wind turbine.

Wind is one of the most widely used renewable energy sources due to its cost-effectiveness, power requirements, operation, and performance. There are many challenges in wind turbines, such as wind fluctuation, pitch control, and generator speed control. When the wind speed exceeds its rated value, the pitch angle controller limits the generator output power to its rated value. In this research work, several soft computing techniques have been implemented for pitch control of variable-speed wind turbine. The data is collected for the National Renewable Energy Laboratory offshore 5 MW baseline wind turbine. Wind speed, tip speed ratio, and power coefficient are taken as inputs, and pitch angle as output. Machine learning and artificial intelligence-based techniques such as recurrent neural networks (RNNs), adaptive neuro-fuzzy inference system (ANFIS), multilayer perceptron feed-forward neural network (MLPFFNN), and fuzzy logic controller (FLC) are implemented on MATLAB, and their results are evaluated in terms of mean square error (MSE) and root mean square error (RMSE). The controllers have been implemented in MATLAB/Simulink to schedule the wind turbine blade pitch angle and keep the output power stable at the rated value. The experimental results show that RNN provided the best results for 15 neurons in hidden layers and 1000 epochs with MSE of 3.28e-11 and RMSE of 5.54e-06, followed by MLPFFNN with MSE of 2.17e-10 and RMSE of 1.56e-05, ANFIS with MSE of 8.5e-05 and RMSE of 9.22e-03, and FLC with MSE of 6.25e-04 and RMSE of 0.025. The proposed scheme is more reliable and robust and can be easily implemented on a physical setup by using interfacing cards such as dSPACE, NI cards, and data acquisition cards.

Robust Reinforcement Learning-Based Multiple Inputs and Multiple Outputs Controller for Wind Turbines

The control of variable-speed wind turbines that generate electricity from the kinetic energy of the wind involves subsystems that need to be controlled simultaneously, namely, the blade pitch angle controllers and the generator torque controllers. The presented study solves the control problem with multiple inputs and multiple outputs (MIMO), using the method of reinforcement learning–based Trust Region Policy Optimization, through which the control parameters of both subsystems are simultaneously optimized. In this case, the robust control problem is transformed into a constrained optimal control problem with an appropriate choice of value functions for the nominal system. The study aims to synthesize a robust controller, with the aim of maximizing the generated energy (power) and minimizing unwanted forces (thrust). The innovative control architecture uses an extended input space, which allows fine-tuning of parameters for each operating state. Test calculations carried out in simulation experiments using models of the 5 MW NREL wind turbine and the 4 MW Enercon E-126 EP3 wind turbine are presented to illustrate the performance and practicality of the proposed approach.

Adaptive Neuro-fuzzy Algorithm for Pitch Control of Variable-speed Wind Turbine

Adaptive Neuro-fuzzy Algorithm for Pitch Control of Variable-speed Wind Turbine

Adaptive active fault-tolerant MPPT control of variable-speed wind turbine considering generator actuator failure

In order to ensure that the wind power system (WPS) can realize maximum power point tracking (MPPT) under generator side fault, an MPPT control system with adaptive active fault tolerance capability is proposed in this paper. The basic idea of the proposed control strategy is that a perturbation term containing model uncertainties, system nonlinearities and unknown disturbances (generator actuator failure and disturbance torque) is estimated in real-time by a designed observer. The estimated perturbation is used for the compensation of actual perturbation. Then, an adaptive feedback linearizing control of variable-speed wind turbine (VSWT) system can be realized. Therefore, the control strategy neither requires detailed system model and full state measurements, nor relies on fault detection, diagnosis and isolation techniques when the generator actuator fails. Simulation results show that the proposed control scheme has smaller tracking error and better dynamic performance than the traditional PI control and MPPT control, and higher robustness against system parameter uncertainties, disturbance torque and generator actuator failure than the nonlinear static state feedback based MPPT (NSSF-MPPT) control, traditional PI control and MPPT control.

Coordinated Wide-Area Damping Control in Modern Power Systems Embedded with Utility-Scale Wind-Solar Plants

This paper presents a coordinated wide-area damping control of power system stabilizers (PSSs), static synchronous compensator (STATCOM), and static synchronous series compensator (SSSC) for grid-forming based wind and solar PV generation resources. The main objective of this work is to enhance the damping for inter-area oscillations while maintaining the voltage and frequency in the prescribed range, taking into consideration the operational uncertainties. Better voltage and reactive power support are provided by the use of STATCOM and for additional damping, an SSSC is employed with the coordinated wide-area damping controller (CWADC). Variable-speed wind turbine control methodology strategically combined with inertia control, de-loading control, pitch angle control, and electronic rotor speed control is employed to obtain an optimum response for discontinuous generation mixes and variable wind speed. The geometric measures of controllability/observability and residues method have been utilized to choose the appropriate input control signals and optimal location of CWADC. A multi-objective salp swarm algorithm has been used to optimize the parameters of the proposed CWADC. To demonstrate the efficacy of the proposed CWADC, nonlinear time-domain simulations are performed on a modified IEEE 68-bus test system embedded with hybrid wind-solar power plants considered multiple time delays.

Optimal control of variable-speed wind turbines modeled as Markov jump systems

This paper shows the solution for the control problem of operating wind turbines through Markov jump nonlinear systems. The idea is to represent wind speed acting on the turbine blades into modes of Markov chain. The main result then characterizes the optimal control for the long-run average cost of turbine operation. As a byproduct, the turbine model becomes second-moment stable, a concept borrowed from the literature of stochastic systems. To illustrate the benefits of our approach, we performed simulations in the FAST 5-MW wind turbine; the simulated data suggest that our control outperform other control strategies from the literature—increasing the produced power by 0.53%.

Actor-critic continuous state reinforcement learning for wind-turbine control robust optimization

The control of Variable-Speed Wind-Turbines (VSWT) extracting electrical power from the wind kinetic energy are composed of subsystems that need to be controlled jointly, namely the blade pitch and the generator torque controllers. Previous state of the art approaches decompose the joint control problem into independent control subproblems, each with its own control subgoal, carrying out separately the design and tuning of a parameterized controller for each subproblem. Such approaches neglect interactions among subsystems which can introduce significant effects. This paper applies Actor-Critic Reinforcement Learning (ACRL) for the joint control problem as a whole, carrying out the simultaneous control parameter optimization of both subsystems without neglecting their interactions, aiming for a globally optimal control of the whole system. The innovative control architecture uses an augmented input space so that the parameters can be fine-tuned for each working condition. Validation results conducted on simulation experiments using the state-of-the-art OpenFAST simulator show a significant efficiency improvement relative to the best state of the art controllers used as benchmarks, up to a 22% improvement in the average power error performance after ACRL training.

New structure of sliding mode control for variable speed wind turbine

This article investigates a new sliding mode control structure for a variable speed wind turbine, in order to maximize the captured wind energy and to reduce the transient loads (shafts vibration) caused by the fast fluctuation of wind speed. The variable speed wind turbine control presents a difficult problem because of the nonlinearities of equivalent mathematical models and the effects of external disturbances (wind speed fluctuation). The sliding mode technique is a nonlinear control, widely used in this field; this is due to its robustness in terms of stability and performance against disturbances and modeling uncertainties, and its simplicity of implementation. However, this technique has a major problem which is the chattering phenomenon caused by the discontinuous portion of its control law. A new structure of sliding mode technique is developed in this paper to overcome this phenomenon and maintain the effectiveness of traditional approach. The performance of the developed control will be offered by numerical simulations and will be compared to the basic method of sliding mode control based on a strong nonlinear model of wind turbine.

Efficacious pitch angle control of variable-speed wind turbine using fuzzy based predictive controller

The Wind energy is more reliable and speedier growing, among the renewable energy resources, due to the world environment challenges as well as increasing demand for energy. The wind turbine system’s stability is cumbersome due to the uneven distribution of wind. Centrifugal and gravitational loads on the blades of a wind turbine creates weariness, resultantly decreases the power output along with the life of the equipment. Therefore, the need for a pitch angle control that can reduce the loading effect in addition to provide maximal power output. This paper proposes the fuzzy based model-predictive controller of pitch angle control to minimize the loading effect on wind turbine by limiting power output and rotor speed to its rated value as well as to maximize the extracted power output as compared to other techniques. The fuzzy logic controller works very efficiently by encountering the system’s non-linearity while model predictive controller helps the system to become more stable and efficient. The superiority of prescribed controller is verified by comparing it with PI controller. The proposed model has been tested in MATLAB/Simulink using a 3MW wind turbine system.

A New Hill Climbing Maximum Power Tracking Control for Wind Turbines With Inertial Effect Compensation

Finding and tracking maximum power point are two important dynamics in the control of variable-speed wind turbines since they determine the efficiency of wind turbines. The conventional hill climbing possesses the problems of wrong directionality and low performance since it does not take the inertial effect into account. In this paper, a novel hill climbing method is proposed by considering the inertial effect to solve these problems. Besides, employing the exact model knowledge of the generator in the maximum power tracking control deteriorates the efficiency considerably; therefore, it is required to design a parameter independent and robust control system if possible. Thus, the third-order super-twisting sliding mode and continuous integral sliding mode controllers are designed for the control of generator and grid-side converters to track the maximum power trajectory accurately, and they are compared to each other for the chattering in experimental results. A comparison is also performed between the conventional and proposed hill climbing methods based on the captured energy from the wind. Experimental results, with a wind turbine emulator, demonstrate that the proposed hill climbing method relaxes the wrong directionality and sluggish performance of the conventional one.

Uncertain Saturated Discrete‐Time Sliding Mode Control for A Wind Turbine Using A Two‐Mass Model

AbstractThe aim of this paper is to propose a new design variable speed wind turbine control by discrete‐time sliding mode approach. The control objective is to obtain a maximum extraction of wind energy, while reducing mechanical loads and rotor speed tracking combined with an electromagnetic torque. For this application, we designed a discrete time sliding mode control using the equivalent discrete time reaching law. Furthermore, a systematic and improved design procedure for uncertainties discrete‐time sliding mode control (SMC) with saturation problem is provided in this paper. The saturation constraint is reported on inputs vector. LMI technique and polytopic models are used in the design of the switching surface. To achieve some performance requirements and good robustness, in the sliding mode, the pole clustering method is investigated. Based on the unit vector control approach, a robust control is developed, then, to direct and maintain the system states onto the sliding manifold in finite time. Finally, a systematic design procedure for DSMC required to achieve a given performance level is provided and its effectiveness is varied by applying it to variable speed wind turbine systems.

Variable speed wind turbine control by discrete-time sliding mode approach

The aim of this paper is to propose a new design variable speed wind turbine control by discrete-time sliding mode approach. This methodology is designed for linear saturated system. The saturation constraint is reported on inputs vector. To this end, the back stepping design procedure is followed to construct a suitable sliding manifold that guarantees the attainment of a stabilization control objective. It is well known that the mechanisms are investigated in term of the most proposed assumptions to deal with the damping, shaft stiffness and inertia effect of the gear. The objectives are to synthesize robust controllers that maximize the energy extracted from wind, while reducing mechanical loads and rotor speed tracking combined with an electromagnetic torque. Simulation results of the proposed scheme are presented.

Internal Model Controller for Variable-Speed Wind Turbines at High Wind Speeds

Internal Model Controller for Variable-Speed Wind Turbines at High Wind Speeds

Fault-Tolerant Optimal Tip-Speed-Ratio Tracking Control of Wind Turbines Subject to Actuation Failures

In this paper, a maximum-power-point-tracking controller for variable-speed wind turbines (VSWTs) is developed, which is shown to be able to account for modeling uncertainties, unexpected disturbances, subsystem failures, and actuation saturation simultaneously. A novel memory-based approach is used to predict wind speed that is used to generate desired rotor speed accordingly. It is shown that the proposed algorithm not only is robust against nonlinear aerodynamics and adaptive to unknown and time-varying inertia/damp/stiffness properties of VSWTs but also is able to accommodate actuator failures under torque constraints. The benefits of the proposed control method are analytically authenticated and demonstrated with Fatigue, Aerodynamics, Structures, and Turbulence code and Simulink.

Practical Advantages of Multivariable Control Strategy for Off-Grid Variable Speed Variable-Pitch (VS-VP) Wind Turbines

The design of variable speed wind turbine control systems is a hard challenge where a nonlinear multivariable process with high disturbances, restrictions and interaction between variables appears. Under that situation, a reliable and powerful control strategy is needed to achieve a maximum performance. In this paper a multivariable control scheme based on a torque controller and pitch angle controller for a VS-VP small wind turbine connected with a permanent-magnet DC generator (PMG) is proposed. Both controllers are tuned for operating in several wind speed regions. Simulation results show the robustness, effectiveness and benefits of the multivariable control strategy used for different operation situations. The multivariable controller is compared with other baseline control schemes such as LQG controller and standard switched controller.

Non-linear control of variable-speed wind turbines with permanent magnet synchronous generators: a robust backstepping approach

In this study, a robust backstepping approach for the control problem of the variable-speed wind turbine with a permanent magnet synchronous generator is presented. Specifically, to overcome the negative effects of parametric uncertainties in both mechanical and electrical subsystems, a robust controller with a differentiable compensation term is proposed. The proposed methodology ensures the generator velocity tracking error to uniformly approach a small bound where practical tracking is achieved. Stability of the overall system is ensured by Lyapunov-based arguments. Comparative simulation studies with a standard proportional-integral-type controller are performed to illustrate the effectiveness, feasibility and efficiency of the proposed controller.

Fully sensorless robust control of variable-speed wind turbines for efficiency maximization

This paper focuses on a sensorless robust power generation control strategy for a variable speed wind energy conversion system based on a permanent magnet synchronous generator. The proposed control strategy combines a robust observer of the aerodynamic torque, a simple technique for extracting rotor position using electrical signals, a robust observer of rotor speed, and a sliding mode based field oriented control strategy. The robust vanishing of the observation errors and tracking error is proved. Reported numerical simulations show that the proposed control policy is effective in terms of efficiency maximization and it is robust with respect to bounded parameter variations affecting the mechanical system.

Nonlinear Dual-Mode Control of Variable-Speed Wind Turbines With Doubly Fed Induction Generators

This paper presents a feedback/feedforward nonlinear controller for variable-speed wind turbines with doubly fed induction generators. By appropriately adjusting the rotor voltages and the blade pitch angle, the controller simultaneously enables: (a) control of the active power in both the maximum power tracking and power regulation modes, (b) seamless switching between the two modes, and (c) control of the reactive power so that a desirable power factor is maintained. Unlike many existing designs, the controller is developed based on original, nonlinear, electromechanically-coupled models of wind turbines, without attempting approximate linearization. Its development consists of three steps: (i) employ feedback linearization to exactly cancel some of the nonlinearities and perform arbitrary pole placement, (ii) design a speed controller that makes the rotor angular velocity track a desired reference whenever possible, and (iii) introduce a Lyapunov-like function and present a gradient-based approach for minimizing this function. The effectiveness of the controller is demonstrated through simulation of a wind turbine operating under several scenarios.

Flicker Mitigation by Active Power Control of Variable-Speed Wind Turbines With Full-Scale Back-to-Back Power Converters

Grid-connected wind turbines are fluctuating power sources that may produce flicker during continuous operation. This paper presents a simulation model of a megawatt-level variable-speed wind turbine with a full-scale back-to-back power converter developed in the simulation tool of PSCAD/EMTDC. Flicker emission of this system is investigated. Reactive power compensation is mostly adopted for flicker mitigation. However, the flicker mitigation technique shows its limits, when the grid impedance angle is low in some distribution networks. A new method of flicker mitigation by controlling active power is proposed. It smoothes the 3p active power oscillations from wind shear and tower shadow effects of the wind turbine by varying the dc-link voltage of the full-scale converter. Simulation results show that damping the 3p active power oscillation by using the flicker mitigation controller is an effective means for flicker mitigation of variable-speed wind turbines with full-scale back-to-back power converters during continuous operation.

Variable Speed Control of Wind Turbines Via Memory-Based Firing Angle Sequence Adjustment

Maximum electric power extraction out of available wind power is directly linked to advanced variable speed wind turbine control. The paper presents a memory-based method for variable speed adjustment of wind energy conversion systems. The fundamental idea behind the method is to use certain memorized information (i.e., current rotor speed tracking error, most recent speed tracking error, and previous control experience) to directly modify the firing angle control command sequences. The salient feature of the proposed approach lies in its simplicity in design and implementation. Furthermore, the total required memory space does not grow with time and is much smaller than most existing learning control methods. It is shown that this method, when applied to firing angle control of wind turbines, is able to ensure rotor speed tracking in the presence of varying operation conditions, as verified via computer simulation.