Variable Speed Wind Turbine System Research Articles

Sliding mode control based on maximum power point tracking for dynamics of wind turbine system

This article presents a proportional-integral sliding mode control (PI-SMC) approach for a two-mass variable speed wind turbine (VSWT) system. Most studies on wind turbines typically focus mainly on the electromagnetic part of the generators, or even on the high-speed part, considering the shaft stiffness as negligible. However, the generator torque is actually driven by the aerodynamic torque, and a two-mass system like the one studied here plays the role of a transmission element for this power. To address this challenge, the problem of low power generation resulting from wind speed variability is tackled by designing a PI-SMC control law, capable of controlling the mechanical turbine model that optimizes power and torque by tracking the maximum power point (MPPT) for rotational speed and aerodynamic power. To validate the developed theoretical results, an application of the wind turbine system is simulated in Matlab/Simulink, for a particular case. The control used is capable of satisfying the dynamic performance of the systems.

Power regulation of variable speed multi rotor wind systems using fuzzy cascaded control

Power quality is a crucial determinant for integrating wind energy into the electrical grid. This integration necessitates compliance with certain standards and levels. This study presents cascadedfuzzy power control (CFPC) for a variable-speed multi-rotor wind turbine (MRWT) system. Fuzzy logic is a type of smart control system already recognized for its robustness, making it highly suited and reliable for generating electrical energy from the wind. Therefore, the CFPC technique is proposed in this work to control the doubly-fed induction generator (DFIG)-based MRWT system. This proposed strategy is applied to the rotor side converter of a DFIG to improve the current/power quality. The proposed control has the advantage of being model-independent, as it relies on empirical knowledge rather than the specific characteristics of the DFIG or turbine. Moreover, the proposed control system is characterized by its simplicity, high performance, robustness, and ease of application. The implementation of CFPC management for 1.5 MW DFIG-MRWT was carried out in MATLAB environment considering a variable wind speed. The obtained results were compared with the direct power control (DPC) technique based on proportional-integral (PI) controllers (DPC-PI), highlighting that the CFPC technique reduced total harmonic distortion by high ratios in the three tests performed (25%, 30.18%, and 47.22%). The proposed CFPC technique reduced the response time of reactive power in all tests by ratios estimated at 83.76%, 65.02%, and 91.42% compared to the DPC-PI strategy. Also, the active power ripples were reduced by satisfactory proportions (37.50%, 32.20%, and 38.46%) compared to the DPC-PI strategy. The steady-state error value of reactive power in the tests was low when using the CFPC technique by 86.60%, 57.33%, and 72.26%, which indicates the effectiveness and efficiency of the proposed CFPC technique in improving the characteristics of the system. Thus this control can be relied upon in the future.

The wind turbine's direct power control of the doubly-fed induction generator

The study suggests a comprehensive approach to modeling and controlling variable-speed wind turbine systems that utilize doubly fed induction generators (DFIGs). To make sure that energy is transferred efficiently between the DFIG rotor and the grid, a two-level inverter with perfect bidirectional switches is used. Using the tip speed ratio algorithm and taking into consideration the randomness in wind speed, the maximum power at the wind turbine is optimized. Then, the control strategy utilizes direct power control (DPC) due to its various advantages. The advantages of employing this control technique are manifold. Firstly, it eliminates the necessity for rotor current control loops. Secondly, it obviates the need for controllers such as PI controllers to manage torque and flux. Furthermore, it has yielded exceptional simulation results when implementing direct power control (DPC) within the MATLAB/Simulink environment, specifically in the context of a doubly fed induction generator (DFIG) wind power system.

Hardware-in-the-loop simulation to validate the fractional-order neuro-fuzzy power control of variable-speed dual-rotor wind turbine systems

New and efficient command strategies and algorithms are needed in the field of wind turbine energy generation to ensure power quality according to international standards. However, conventional linear strategies are still used to command doubly-fed induction generators (DFIGs). Thus, inadequate power quality is obtained, which can cause network-level disturbances. This Hardware-in-the loop (HIL) study presents a new command scheme for a DFIG-based dual-rotor wind turbine (DRWT) system. The new command is a combination of a neuro-fuzzy algorithm and fractional-order control that overcomes the declining power quality of the DFIG-DRWT system. The new strategy is based on using pulse width modulation to generate command pulses for the rotor-side converter of DFIG. In the designed command system, the reference value of the active power is determined using maximum power point tracking to provide efficient power conversion performance under different operating conditions. First, MATLAB software is used to implement the fractional-order neuro-fuzzy (FONF) control technique, and the behavior of the proposed strategy is studied in comparison to that of the traditional direct power command (DPC) technique. A comparison is performed in terms of the ripple minimization ratio, durability, overshoot, steady-state error, reference tracking, and current quality. The results of the comparison show the high performance of the FONF technique. Second, the FONF technique is implemented in HIL test using the dSPACE 1104 Card, where two different forms of wind speed are used to study the characteristics of the proposed strategy and confirm its effectiveness and performance in HIL test compared to DPC technique. The experimental results obtained in the two tests confirm the efficiency, effectiveness, and high performance of the proposed FONF technique compared to DPC technique in improving the energy system characteristics, and the simulation obtains the same results.

Optimal captured power control of variable speed wind turbine systems: Adaptive dynamic programming approach

SummaryAn adaptive optimal controller is proposed in this paper to maximize the captured power of a variable speed wind power system. The proposed controller is a combination of optimal and adaptive control components. The Adaptive Dynamic Programming technique is used to design the optimal control component to overcome the nonlinear problem of system dynamics and ensure stability. While the neural network is used to approximate unknown disturbances and system uncertainties. After that, the adaptive control component fully compensates for the effects of these unknown elements. Neither optimal nor adaptive control components necessitate prior knowledge of system dynamics. Furthermore, the approximation network updates only the weight matrix norm rather than the weight matrix of the neural network in each interval time, which significantly reduces computation. The stability analysis of the closed‐loop system is obtained using Lyapunov stability theory. The correctness and robustness of the control scheme are validated in two different scenarios using MATLAB/Simulink. The presented robust adaptive optimal controller is also compared to other existing controllers to demonstrate its benefits.

Pitch angle control of wind turbines using model-free auto-tuned fractional order proportional derivative ATFOPD controller

The nonlinear dynamics of wind power plants, in addition to uncertainties such as unknown nonlinear disturbances and parameter variations make the design of a robust controller a difficult task. This paper proposes a robust fractional-order controller for the pitch angle control of a variable-speed wind turbine system. An auto-tuned fractional order proportional-derivative controller ATFOPD is designed taking the objectives of reducing pitch actuator fatigue, limiting output mechanical power and speed at their rated values above the rated wind speed. The phase, phase slope and modulus of the pitch actuator process at the fixed gain crossover frequency are needed in order to tune the fractional order controller parameters. These values are usually derived using a mathematical model of the system, such as a transfer function. A model-free auto-tuning technique that can calculate the controller's parameters from measured variables is used in this work in order to design a robust FOPD controller. Simulation results of the ATFOPD controlled system are compared to integer order proportional-derivative IOPD and IOPID controllers, which show that the ATFOPD controller is more effective than the other controllers and its robustness is verified in the presence of disturbances in addition to system parameters and wind speed variations.

Active and reactive power vector control using neural-synergetic-super twisting controllers of induction generators for variable-speed contra-rotating wind turbine systems

Reactive and active power vector control of induction generators (IG) are essential requirements for generating high-quality electricity from wind power. These control objectives are challenging and difficult to achieve when using traditional strategies based on estimating reactive/active power, hysteresis comparators, and proportional-integral (PI) regulators due to load variations, changes in the value of rotor resistance, etc. So, to achieve these control objectives, this paper proposes a novel technique for the rotor side converter of IG-based contra-rotating wind power (CRWP) systems. The control based on the neural synergetic-super-twisting controller (NSSTC) is designed to minimize IG power ripples and improve the quality of current. The characteristics of the NSSTC-based strategy are presented, evaluated, and compared to the traditional direct field-oriented command (DFOC) based on traditional PI controllers and other reference techniques from the literature, highlighting that the NSSTC-based strategy is simpler to apply and more robust and performant than others classical nonlinear strategies. Comparative simulations are carried out on both the designed DFOC-NSSTC strategy and the DFOC technique to demonstrate the performance (good quality output power, low total harmonic distortion (THD) value of rotor currents, short response time and high robustness) and advantages of the suggested nonlinear technique.

Adaptive optimal secure wind power generation control for variable speed wind turbine systems via reinforcement learning

As the utilization of wind energy continues to grow, it is crucial to prioritize the identification of vulnerabilities, raise awareness, and develop strategies for cybersecurity defense. False data injection (FDI) attacks, if targeted at the communication between the rotor speed sensor and the wind turbine (WT) controller, can potentially disrupt the normal operation of the system. These attacks have the capability to overload the drive-train and significantly reduce the power generation efficiency of the wind turbine. So, this note presents an adaptive optimal secure control strategy entailing reinforcement learning (RL) neural network (NN) using the filter error to compensate the detrimental effects of FDI attack as well as actuator fault for WT systems. The Hamilton–Jacobi–Bellman (HJB) equation is constructed and solved to obtain the optimal control policy. Since the HJB is inextricably intertwined with intrinsic nonlinearity and complexity, solving this equation is quiet challenging. To tackle this issue and also approximate the solution of the HJB, an actor–critic-based reinforcement learning (RL) strategy is used, in which actor and critic NNs are applied to execute control action and assess control performance, respectively. To detect FDI attack, an anomaly detection is developed using a nonlinear observer/estimator. Stability analysis is performed using Lyapunov theory which guarantees semi-global uniformly ultimately bounded (SGUUB) of the error signal. Finally, simulation results verify the effectiveness of the proposed control approach.

Optimized fuzzy PI controller for variable speed wind turbine using DE algorithm

To design an optimal fuzzy proportional-integral (PI) controller for the variable speed wind turbine systems, a new differential evolution (DE) algorithm approach is developed in this paper. We have investigated a fuzzy PI controller, in which fuzzy rules are applied to adapt the parameters of the PI controller founded on the error and its first-time derivative. The fuzzy PI controller's inputs and outputs are tuned using the DE optimization method. The superiority of the suggested (DE fuzzy PI) controller has been proved by comparing the results with (fuzzy PI) and only the PI controller applied to the wind turbine system. In comparison to a fuzzy controller with parameters selected by a human operator, the numerical validation results of the suggested approach (DE fuzzy PI) have shown good performance in terms of robustness, pursuit, and response time.

Robust sensor-less sliding mode of second-order control of doubly fed induction generators in variable speed wind turbine systems based on a novel MRAS-ANFIS observer

The current study proposed a robust sensor-less sliding mode second-order based on a super twisting algorithm (STA-SMSO) approach using a new observer Model Reference Adaptive System-Adaptative Neuro-Fuzzy Inference System (MRAS-ANFIS). This model was applied to a doubly fed induction generator (DFIG) wind turbine running under variable wind speed and DFIG fed with a power voltage source without a speed sensor, while the control objective was used to regulate independently, the active and reactive power DFIG stator were decoupled by using the field-oriented control technique. Additionally, this process reduced the cost of the control scheme and the size of DFIG by eliminating the speed sensor (encoder). In order to improve the traditional MRAS, the MRAS-ANFIS observer was proposed to replace the usual PI controller in the adaptation mechanism of MRAS with an Adaptative Neuro-Fuzzy Inference System (ANFIS) controller. The estimation of rotor position was tested and discussed under varying load conditions in low, zero, and high-speed region. The results mentioned that the proposed observer (MRAS-ANFIS) presented an attractive feature, such as guarantees finite time convergence, good response on speed wind variations, high robustness against machine parameter variations, and load variations compared to the conventional MRAS observer and MRAS-Fuzzy. Hence, the estimated rotor speed converged to their actual value has the capacity for estimating position in deferent region (low/zero/high) of speed.

Optimal control for wind turbine based on reinforcement learning

In this conference paper, an optimal control method is designed for a variable speed wind turbine system. Due to the inherent nonlinearity of the wind turbine arising from the aerodynamic torque, a linearized model is derived to handle the system's nonlinearities. An online update cost function is created based on the resulting linearized model. The critic neural network weight vector is updated with the steepest decent algorithm to design an optimal control able to minimize the given cost function. To validate the effectiveness of the optimal control based on reinforcement learning, simulation results with varying wind speed profile for different values of learning parameters are presented.

Coordination of Enhanced Control Schemes for Optimal Operation and Ancillary Services of Grid-Tied VSWT System

Wind power’s increasing use and its integration into the utility grid have prompted scholars to focus more on the refinement of wind power harvesting systems, injecting stable power and providing ancillary services to the utility grid. This article introduces a novel hybrid approach termed as sine cosine algorithm and transient search optimization (HSCATSO) optimizer of better exploration and exploitation phases for optimal designing the power electronic converter control schemes (PECCS) of the grid-tied variable speed wind turbine (VSWT) system. The PECCS is simultaneously coordinated with a robust maximum power extraction algorithm (MPEA) to form enhanced control systems for achieving the best wind harnessing, improving the VSWT system performance, and supporting the utility grid stability. In this context, the HSCATSO optimally designs the PECCS parameters based on minimizing the summation of integral squared error (ISE) of multiple error signals in the developed control schemes in coordination with the MPEA. The superiority of the HSCATSO optimizer is validated using twenty benchmark functions and statistically analysed against four well-known optimization algorithms. Meanwhile, the effectiveness of the optimally designed PECCS using the HSCATSO is verified by the extensive simulation analysis in MATLAB/Simulink considering severe grid disturbance and real wind speed data taken from Kudat, Sabah, Malaysia to mimic realistic circumstances. The obtained results have been compared with that realized using the other algorithms-based design PECCS. The simulation outcomes affirmed that the PECCS designed by the HSCATSO and coordinated with MPEA resulted in higher power harvesting and enhanced the grid-tied VSWT system stability better than the competitive control schemes.

Network‐based robust exponential fuzzy control for uncertain systems

This article studies the robust exponential stability and Takagi–Sugeno (T–S) fuzzy control synthesis for networked control systems via performance. The main aim of this paper is to design fuzzy controllers with less conservative results. Novel weighted integral inequalities (WIIs) are proposed based on Wirtinger's integral inequalities. The T–S fuzzy approach expresses nonlinear systems as linear submodels with IF–THEN rules for deriving the stability conditions. Then, by constructing a suitable Lyapunov–Krasovskii functional (LKF) and applying new WIIs, improved exponential stability and stabilization criteria are established in the form of linear matrix inequalities (LMIs). Three examples are provided to demonstrate the advantages and usefulness of the proposed novel method. Two are application‐oriented examples, such as the variable speed wind turbine (VSWT) system and nonlinear mass‐spring (NMS) system.

Dissipative-based sampled-data control for T-S fuzzy wind turbine system via fragmented-delayed state looped functional approach

This study investigates thedissipative-based fuzzy sampled-data control scheme for variable-speed wind turbine system (WTS) by fragmented-delayed state looped functional framework. The main objective of this study is to stabilize the nonlinear variable-speed WTS and enhance its dynamic performance. To do this, initially, the proposed nonlinear variable-speed WTS is transformed into linear subsystems based on the Takagi–Sugeno (T-S) fuzzy approach. Then, the concept of coupling leakage time-varying delay is proposed to construct a more generalized T-S fuzzy model. After that, to minimize design conservatism, an improved fragmented- delayed state looped-Lyapunov functional is developed to fully utilize the advantages of the variable characteristics related to the actual sampling pattern. Besides, by applying the proposed new integral inequalities, some sufficient conditions are derived to ensure the addressed system is asymptotically stable under an optimizing performance index. Finally, numerical simulations are given to verify the effectiveness and feasibility of the proposed control scheme. The essential outcome of the proposed approach is that it can provide a superior dissipative performance index under the maximal sampling period.

A direct vector control based on modified SMC theory to control the double-powered induction generator-based variable-speed contra-rotating wind turbine systems

The current and active power ripples are two of the biggest drawbacks of the direct vector control (DVC), as these ripples cause several problems in the electric power generation system from contra-rotating wind turbines (CRWTs) systems. But the DVC technique has multiple advantages that make it among the most widely used techniques in the field of renewable energies for its ease to implementation and simplicity. In this work, a modified sliding mode controller (MSMC) was proposed and applied in the DVC strategy. The combination of the DVC and MSMC controller leads to a more robust control scheme, thus reducing the current, torque, active power, and reactive power ripples of the double-powered induction generator (DPIG). The designed DVC-MSMC strategy is used to improve the performance of the DPIG-based CRWT system. Simulation results done in Matlab software show the effectiveness and robustness of the proposed technique.

Sensorless passivity based control of doubly-fed induction generators in variable-speed wind turbine systems based on high gain observer

The current study presents a robust sensorless control using passivity based control (PBC) combined with high gain observer (HGO). The proposed controller is applied to control the generated doubly-fed induction generator (DFIG) active and reactive power installed on a variable speed wind energy conversion system. The control objective is used to regulate independently the DFIG stator active and reactive power, which are decoupled by using the field oriented control technique. Additionally, this process leads to reduce the cost of control scheme by eliminating the speed sensor. Firstly, the DFIG is modeled under the port controlled Hamiltonian (PCH) model, as well as the method of simultaneous injection damping. Then, the DFIG is further modeled by assignment passivity based on the simultaneous injection damping and assignment (SIDA-PBC) control of the obtained model under such conditions and a comparison with the fuzzy sliding mode controller is carried out. Furthermore, the HGO is selected in order to estimate the rotor position and the speed from the measurement of the DFIG currents and voltages, and compared with fuzzy sliding mode observer. For testing the proposed control scheme performance, a 1.5 MW DFIG system is developed and simulated using MATLAB/Simulink. The obtained results demonstrate the effectiveness of the proposed control scheme in the presence of various DFIG parameters variation. Additionally, the control objective is achieved without speed sensor.

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.

Error-Based Active Disturbance Rejection Control for Pitch Control of Wind Turbine by Improved Coyote Optimization Algorithm

Wind energy systems are expected to supply the majority of future generation from renewables due to the maturity of technology and the availability of energy resources. In this paper, in order to improve the ability of tracking a desired power reference at high wind speed region, a pitch control strategy based on error-based active disturbance rejection control (ADRC) approach is proposed for variable speed wind turbine system, providing a novel practically appealing control structure. The stability analysis of the proposed pitch controller based on singular perturbation theory is provided. Next, an improved coyote optimization algorithm (COA) fused with L <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rm {\acute{e}}$</tex-math></inline-formula> vy flight and Sinusoidal map is proposed to address the controller parameters tuning issue. Then, the effectiveness of the proposed solution is verified on a 1.5 MW FAST simulator taking into account both multi-step and IEC turbulence wind conditions. Finally, an analysis in frequency domain of the pitch control system with the proposed control strategy is presented.

A novel scheme for control by active and reactive power utilized in gearless variable speed wind turbine system with PMSG connected to the grid

Introduction. As a result of increasing fossil fuel price and state-of-the-art technology, more and more residential and commercial consumers of electricity have been installing wind turbines. The motivation being to cut energy bills and carbon dioxide emissions. Purpose. The main goal of this work is developing a control scheme for a variable speed wind turbine generator in order to produce utmost power from varying wind types, and variable wind speed. Novelty. This research paper presents an IGBT power converter control scheme for active power in relation to wind speed and reactive power by adjusting Q-reference (Qref) value in a gearless variable speed wind turbine with permanent magnet synchronous generator. Methods. An effective modelling and control of the wind turbine with the suggested power converter is executed by utilizing MATLAB/Simulink software. The control scheme consists of both the wind turbine control and the power converter control. Simulation results are utilized in the analysis and deliberation of the ability of the control scheme, which reveals that the wind turbine generator has the capability to actively sustain an electric power grid network, owing to its ability to independently control active and reactive power according to applied reference values at variable wind speed. Practical value. This research can be utilized for assessing the control methodology, the dynamic capabilities and influence of a gearless variable-speed wind energy conversion system on electric power grids. A case study has been presented with a (3×10 MW = 30 MW) wind farm scheme.

Hybrid Intelligent Feedforward-Feedback Pitch Control for VSWT With Predicted Wind Speed

Although wind power has gained tremendous development in recent years, how to achieve mechanical loads optimization to extend service life-time of wind turbines is still a hot and challenging topic. In this study, artificial intelligence and advanced control techniques are combined to approach this objective for variable-speed wind turbine systems operating in high-speed region. First, the real-time information of effective wind speed is extracted and predicted via support vector regression (SVR) by exploiting data stream acquired online. Optimization of the support vector regression’s parameters is completed by the particle swarm optimization algorithm. Subsequently, the predicted wind speed is routed to a novel feedforward mechanism designed to build a nonlinear relationship between wind speed and pitch angle. Additionally, an uncertainty and disturbance estimator (UDE) based feedback controller is implemented to deal with the model uncertainties and external disturbances. Both loads optimization and rotor speed/generator power regulation are achieved via strict math analysis. Finally, extensive comparison studies between the proposed scheme and traditional pitch angle controllers are conducted on GH bladed platform to verify the feasibility and effectiveness of the proposed scheme.