Wind Turbine Control System Research Articles

A Review on Popular Control Applications in Wind Energy Conversion System Based on Permanent Magnet Generator PMSG

There has always been a high expectation that wind generation systems would capture maximum power and integrate properly with the grid. Utilizing a wind generation system with increased management to meet the growing electricity demand is a clever way of accomplishing this. However, wind power generation systems require a sophisticated, unique, and dependable control mechanism in order to achieve stability and efficiency. To improve the operation of the wind energy conversion method, researchers are continually addressing the obstacles that presently exist. Therefore, it is necessary to know which control can improve the whole system’s performance and ensure its successful integration into the network, despite the variable conductions. This article examines wind turbine control system techniques and controller trends related to the permanent magnet synchronous generator. It presents an overview of the most popular control strategies that have been used to control the PMSG wind power conversion system. Among others, we mention nonlinear sliding mode, direct power, backstepping and predictive currents control. First, a description of each control is presented, followed by a simulation performed in the Matlab/Simulink environment to evaluate the performance of each control in terms of reference tracking, response time, stability and the quality of the signal delivered to the network under variable wind conditions. Finally, to get a clear idea of the effect of each control, this work was concluded with a comparative study of the four controls.

Numerical study of the effects of pulsed plasma actuator on physical behavior of the fluid flow around a ducted wind turbine

As with other types of wind turbines, the ducted wind turbine has a bright future. On the other hand, flow separation has a consistent effect on this type of turbine, resulting in aerodynamic losses and load fluctuations. As a result, flow control systems for ducted wind turbines are critical for improving aerodynamic performance. Additionally, in this technological age, noise pollution has developed into a serious problem that must be minimized and controlled to the greatest extent feasible. This research investigates the impact of a plasma actuator as an active control approach on the flow dynamics on the blades using a finite volume code. To decrease computing costs, the URANS model and mesh adaptive methods are applied. The numerical results are confirmed by comparing them to a previously collected experimental dataset. The flow dynamics and noise emission of a micro dielectric-barrier-discharge plasma actuator were examined under the impact of discontinuous pulsing. This actuator was fitted in three distinct places at the beginning point of separation in the blade without using the ducted wind turbine’s control approach. The results indicated that positioning the actuator near the blades’ tip improves aerodynamic performance. Additionally, when the plasma actuator’s power is raised, the vortex cancellation is maximized. The results indicated that the DBD actuator generated a considerable portion of reverse flow, in this case in the opposite direction to the tip flow. The reverse flow was used to alter the pressure gradient in the tip gap area, thereby eliminating the vortex. Also, using the plasma actuator reduces the ducted wind turbine’s noise output by cutting down on the wake zone and vortices, which are the main sources of noise.

A New combined MPPT-Pitch Angle control of a Large Variable Speed Wind Turbine in Different Operating Areas based on Synergetic control

The aim of this paper is to create a novel combination between two controls, maximum power point tracking (MPPT) and Pitch angle control system of a variable-speed wind turbine. The main objective sought is to achieve the maximization of the power produced by the fixed pitch angle turbine through the MPPT control in the zone 02 of operation. Then, limit the power to its nominal value by using the Pitch control with variable pitch angle in zone 03 of operation. Our contribution will be to propose strategies based on two types of controllers. The first is the control by the MPPT control, it is applied in light winds to extract the maximum power. The second is Variable Pitch Control, which is applied in strong winds to keep power constant at its nominal value, as well as protecting the wind turbine from high winds. For this, linear and non-linear control laws (PI, SC) respectively are implemented to achieve the defined objective. The simulation results show the feasibility and effectiveness of the techniques used.

Impact of Canonical Perturbations in the Inflow on Wind Turbine Loads

The turbulent velocity field in the atmospheric boundary layer creates inflow fluctuations at a wide range of spatial and temporal scales that must be considered for resilient turbine design. This study is focused on separately characterizing the wind turbine’s response to canonical spatial or temporal oscillations in the inflow with only one wavelength or frequency. Temporal fluctuations in the inflow produce a response that is up to an order of magnitude greater than that of purely spatial fluctuations. The response to spatial oscillations in the inflow is also highly dependent on the alignment of the spatial waveform in the inflow to the rotor hub (i.e. phase angle). Different phase angles produced up to a factor of 30 difference in load variations. The integrated wind turbine loads show the largest response to spatial oscillations at wavelengths around 100-140m which is approximately four times the response at the chord scales. Structural deformations largely dampen the response to spatial oscillations in the inflow while increasing the response to temporal fluctuations near the blade rotation frequency. The wind turbine control system also amplifies the load response to temporal oscillations near the blade rotation frequency.

Load reduction for wind turbines: an output-constrained, subspace predictive repetitive control approach

Abstract. Individual pitch control (IPC) is a well-known approach to reduce blade loads on wind turbines. Although very effective, IPC usually requires high levels of actuator activities, which significantly increases the pitch actuator duty cycle (ADC). This will subsequently result in an increase of the wear on the bearings of the blades and a decrease of the wind turbine reliability. An alternative approach to this issue is to reduce the actuator activities by incorporating the output constraints in IPC. In this paper, a fully data-driven IPC approach, which is called constrained subspace predictive repetitive control (cSPRC), is introduced. The output constraints can be explicitly considered in the control problem formulation via a model predictive control (MPC) approach. The cSPRC approach will actively produce the IPC action for the necessary load reduction when the blade loads violate the output constraints. In this way, actuator activities can be significantly reduced. Two kinds of scenarios are simulated to illustrate the unique applications of the proposed method: wake–rotor overlap and turbulent sheared wind conditions. Simulation results show that the developed cSPRC is able to account for the output constraints into the control problem formulation. Since the IPC action from cSPRC is only triggered to prevent violating the output constraints, the actuator activities are significantly reduced. This will help to reduce the pitch ADC, thus leading to an economical viable load control strategy. In addition, this approach allows the wind farm operator to design conservative bounds to guarantee the safety of the wind turbine control system.

Model Predictive Control With a Cascaded Hammerstein Neural Network of a Wind Turbine Providing Frequency Containment Reserve

This article presents an application of neural network-based Model Predictive Control (MPC) to improve the wind turbine control system’s performance in providing frequency control ancillary services to the grid. A closed-loop Hammerstein structure is used to approximate the behavior of a 5MW floating offshore wind turbine with a Permanent Magnet Synchronous Generator (PMSG). The multilayer perceptron neural networks estimate the aerodynamic behavior of the nonlinear steady-state part, and the linear AutoRegressive with Exogenous input (ARX) is applied to identify the linear time-invariant dynamic part. Using the specific structure of the Cascade Hammerstein design simplifies the online linearization at each operating point. The proposed algorithm evades the necessity of nonlinear optimization and uses quadratic programming to obtain control actions. Eventually, the proposed control design provides a fast and stable response to the grid frequency variations with optimal pitch and torque cooperation. The performance of the MPC is compared with the gain-scheduled proportional-integral (PI) controller. Results demonstrate the effectiveness of the designed control system in providing Frequency Containment Reserve (FCR) and frequency regulation in the future of power systems.

OBSO Based Fractional PID for MPPT-Pitch Control of Wind Turbine Systems

In recent times, wind energy receives maximum attention and has become a significant green energy source globally. The wind turbine (WT) entered into several domains such as power electronics that are employed to assist the connection process of a wind energy system and grid. The turbulent characteristics of wind profile along with uncertainty in the design of WT make it highly challenging for prolific power extraction. The pitch control angle is employed to effectively operate the WT at the above nominal wind speed. Besides, the pitch controller needs to be intelligent for the extraction of sustainable secure energy and keep WTs in a safe operating region. To achieve this, proportional–integral–derivative (PID) controllers are widely used and the choice of optimal parameters in the PID controllers needs to be properly selected. With this motivation, this paper designs an oppositional brain storm optimization (OBSO) based fractional order PID (FOPID) design for sustainable and secure energy in WT systems. The proposed model aims to effectually extract the maximum power point (MPPT) in the low range of weather conditions and save the WT in high wind regions by the use of pitch control. The OBSO algorithm is derived from the integration of oppositional based learning (OBL) concept with the traditional BSO algorithm in order to improve the convergence rate, which is then applied to effectively choose the parameters involved in the FOPID controller. The performance of the presented model is validated on the pitch control of a 5 MW WT and the results are examined under different dimensions. The simulation outcomes ensured the promising characteristics of the proposed model over the other methods.

Design and Implementation of an Intelligent Blade Pitch Control System and Stability Analysis for a Small Darrieus Vertical-Axis Wind Turbine

A few studies have been conducted recently in order to improve the aerodynamic performance of Darrieus vertical-axis wind turbines with straight blades (H-type VAWTs). The blade pitch angle control is proposed to enhance the performance of H-type VAWTs. This paper aims to investigate the performance of an H-type VAWT in terms of its power output and self-starting capability using an intelligent blade pitch control strategy based on a multi-layer perceptron artificial neural network (MLP-ANN) method. The performance of the proposed blade pitch controller is investigated by adding a conventional controller (PID) to the MLP-ANN controller (i.e., a hybrid controller). The dynamics of an H-type VAWT is mathematically modeled in a nonlinear state space for the stability analysis in the sense of Lyapunov. The effectiveness of the proposed pitch control system is validated by building an H-type VAWT prototype model that is extensively tested outdoors under different conditions for both fixed and variable pitch angle configurations. Results demonstrated that the blade-pitching technique enhanced the power output of an H-type VAWT by approximately 22%. The hybrid controller that used a high percentage of the MLP-ANN controller achieved a better control performance by reducing the overshoot of the control response at high rotor speeds.

An internal parallel capacitor control strategy for DC-link voltage stabilization of PMSG-based wind turbine under various fault conditions

In recent years, wind energy conversion systems (WECSs) have been growing rapidly. Due to various advantages, a permanent magnet synchronous generator (PMSG) is an appealing solution among different types of wind generators. As wind power penetration level in the grid increases, wind power impacts the grid and vice versa. The most essential concerns in the system are voltage sag and swell, and grid code compliance, particularly for low voltage ride-through (LVRT) and high voltage ride-through (HVRT) capability, is a pressing necessity. This paper presents a parallel capacitor (PC) control strategy to enhance the LVRT and HVRT capability of PMSG. Furthermore, this study presents a method for the sizing of a PC system for the reduction of the overvoltage of the DC-link during voltage sags and swell. Fast Fourier transform analysis is used to determine the total harmonic distortion (THD) for the injected current into the grid. The obtained results illustrate the effectiveness of the proposed system in keeping the DC-link voltage below the limit, power quality improvement, and increasing the LVRT and HVRT capability. Models of wind turbine, PMSG, and PC control system are built using MATLAB/SIMULINK software.

Design of an adaptive controller for double-fed induction wind turbine power

The doubly-fed induction wind turbine has gradually become the mainstream model of wind power generation. Power control is one of the advantages of doubly-fed induction wind generators and has been widely studied. However, existing power control strategies for these turbines have issues with low efficiency. An adaptive control method is proposed in this work, aiming at the power control system of doubly-fed induction wind turbines. Firstly, the power model is obtained, and then the adaptive controller is designed according to the model. Finally, simulation results verify the effectiveness of this method.

Influence of Continuous Provision of Synthetic Inertia on the Mechanical Loads of a Wind Turbine

In many electrical grids, the share of renewable energy generation increases. As these generators are typically connected to the grid via inverters, the level of grid inertia decreases. Such grids may therefore suffer from high rates of change of frequency during power imbalances. Modern wind turbines can help in controlling the frequency in such grids by providing synthetic inertia. A controller to provide synthetic inertia with wind turbines was developed at the Wind Energy Technology Institute in collaboration with Suzlon Energy. For this controller the influence of providing synthetic inertia on the mechanical loads of the wind turbine is assessed for different grid frequency scenarios. Such a scenario-based load analysis has not been published before, especially as the scenarios are derived from real measurements. The effect of the loads strongly depends on the analyzed grid frequency behavior. Ten months of high quality grid frequency measurements of the Indian grid are analyzed in order to derive inputs for the load calculation. Different types of grid frequency abnormities are identified and categorized with respect to their severity. Based on the observed occurrences of the grid frequency abnormities, realistic scenarios for the load calculations are chosen. The load calculations are performed for a state-of-the-art Suzlon wind turbine generator. The load increases caused by the supply of synthetic inertia are calculated for individual components assuming an otherwise undisturbed power production of the wind turbine in turbulent wind. Furthermore, a hardware-in-the-loop test bench is used to show how the measured grid frequencies are actually perceived by the control system of a typical wind turbine. The original frequency data were recorded with high quality measurement equipment, which is faster and more accurate than a multi-function relay, often used in wind turbines. For exemplary time traces, the effect of the reduced measurement accuracy on the reaction of the wind turbine is shown. This aspect has not been investigated in the literature yet. The results show that wind turbines can provide synthetic inertia without a considerable effect on the lifetime of the wind turbine. However, there are still problems with providing synthetic inertia reliably at high power operating points, which have to be solved.

Review of Vibration Control Methods for Wind Turbines

The installation of wind energy increased in the last twenty years, as its cost decreased, and it contributes to reducing GHG emissions. A race toward gigantism characterizes wind turbine development, primarily driven by offshore projects. The larger wind turbines are facing higher loads, and the imperatives of mass reduction make them more flexible. Size increase of wind turbines results in higher structural vibrations that reduce the lifetime of the components (blades, main shaft, bearings, generator, gearbox, etc.) and might lead to failure or destruction. This paper aims to present in detail the problems associated with wind turbine vibration and a thorough literature review of the different mitigation solutions. We explore the advantages, drawbacks, and challenges of the existing vibration control systems for wind turbines. These systems belong to six main categories, according to the physical principles used and how they operate to mitigate the vibrations. This paper offers a multi-criteria analysis of a vast number of systems in different phases of development, going from full-scale testing to prototype stage, experiments, research, and ideas.

Design and simulation of Lidar based control system for wind turbine

Renewable energy sources could be the main contributor to fulfilling the world’s energy requirement. Wind energy is grabbing the world’s attention due to its abundant nature and reliability. Wind energy is a prominent renewable energy source due to its availability and higher reliability. Despite the aforementioned benefits, there are some challenges such as wind measurement and prediction due to the turbulent nature of the wind. Lidar (light detection and ranging) technology is used in wind turbines to preview the wind and act it accordingly. Wind speed along with the direction is measured by the Lidar before it reaches the wind turbine plane and the control system of the wind turbine utilizes this data for optimal results. It enhances the control system along with it optimizes the output power. This paper presents the Lidar simulation model, which previews the wind earlier than the conventional feedback method. The Lidar simulation model is prepared and implemented on the horizontal axis wind turbine. The simulation is performed in GH Bladed at a 2.0 MW wind turbine. The output results are analyzed with the former method. The power extracted, pitch angle, rotor torque obtained from the proposed methodology proves its efficacy.

Performance Characteristics of A Micro Wind Turbine Integrated on A Noise Barrier

Micro wind turbines can be structurally integrated on top of the solid base of noise barriers near highways. A number of performance factors were assessed with holistic experiments in wind tunnel and in the field. The wind turbines underperformed when exposed in yawed flow conditions. The theoretical cosθ theories for yaw misalignment did not always predict power correctly. Inverter losses turned out to be crucial especially in standby mode. Combination of standby losses with yawed flow losses and low wind speed regime may even result in a net power consuming turbine. The micro wind turbine control system for maintaining optimal power production underperformed in the field when comparing tip speed ratios and performance coefficients with the values recorded in the wind tunnel. The turbine was idling between 20%–30% of time as it was assessed for sites with annual average wind speeds of three to five meters per second without any power production. Finally, the field test analysis showed that inadequate yaw response could potentially lead to 18% of the losses, the inverter related losses to 8%, and control related losses to 33%. The totalized loss led to a 48% efficiency drop when compared with the ideal power production measured before the inverter. Micro wind turbine’s performance has room for optimization for application in turbulent wind conditions on top of noise barriers.

Field testing of multi-variable individual pitch control on a utility-scale wind turbine

The ongoing increase in size of modern wind turbines creates the demand of better control algorithms to counteract the increased loads acting on them. Individual blade pitch control (IPC) algorithms to alleviate blade loads are becoming a crucial part of current wind turbine control systems. The state-of-the-art individual blade pitch load reduction controller mostly relies on multiple single-input single-output (SISO) designs. This approach, however, constrains the achievable bandwidth of the controller as relevant couplings in the dynamics are ignored. These couplings become more pronounced for bigger turbines. Model-based multiple-input multiple output (MIMO) control designs can be used to account for these couplings and hence reduce loads for future, larger turbines. In this article we present the results of an intensive field test campaign of an H∞-design based MIMO IPC. This controller is designed for and tested on the utility-scale 2.5 MW Clipper Liberty research turbine operated by the University of Minnesota. The article guides the reader through the turbine’s open loop dynamics, the IPC design and the relevant implementation steps on the turbine. Finally, the developed H∞-based IPC is compared using experimental field data against no IPC (collective blade pitch control) and a classical IPC based on decoupled SISO loops.

Optimization of the Yaw Control Error of Wind Turbine

Yaw system is an important part of wind turbine control system, yaw error is an important performance index of wind turbine, which has great influence on power generation. The wind utilization and the output of the power generation have been determined by the yaw error. In order to make the wind turbine better aligned toward the wind direction, reduce the yaw error, and increase the power generated by the unit, the angle errors of yaw control of wind turbine have been analyzed, in this paper, and the method of wind test, the strategy of yaw control have been studied respectively. Based on the results of the study, the method of wind test, the restart control strategy of yaw system and the performance of control strategy of yaw system have been optimized in this paper. In this way, the three important links are optimized, it will effectively reduce the yaw error as well as significantly improve the wind turbine generating electricity.

Stability analysis of pitch angle control of large wind turbines with fractional order PID controller

This article proposes a robust delay dependent stability analysis of pitch control system of large wind turbines (LWTs) having communication time delay with fractional order PID controller. Fractional order proportional integral and derivative (FOPID) controller is used for pitch angle control. To analyze gain and phase margins effect, a gain and phase margins (GPMs) tester is added to the control path of the large wind turbine (LWT). An exact method in frequency domain is applied for the stability analysis of the LWT. Appropriate selection of FOPID controller parameters, large delay margins are obtained with respect to previous studies. A more robust control scheme is presented and analyzed with different operating conditions. As compared to literature studies, larger time delay margin is obtained. Moreover, in terms of control systems performance metrics better results are obtained with respect to previous studies in the literature. Validation of theoretical results are verified by simulations in Simulink/Matlab environment under various operating conditions. Also, delay margin accuracy is compared with the results obtained from Quasi-Polynomial Mapping Based Root finder (QPmR) method. The results show that better delay margin results are obtained with respect to previous studies.

Alarms management by supervisory control and data acquisition system for wind turbines

Wind energy is one of the most relevant renewable energy. A proper wind turbine maintenance management is required to ensure continuous operation and optimized maintenance costs. Larger wind turbines are being installed and they require new monitoring systems to ensure optimization, reliability and availability. Advanced analytics are employed to analyze the data and reduce false alarms, avoiding unplanned downtimes and increasing costs. Supervisory control and data acquisition system determines the condition of the wind turbine providing large dataset with different signals and alarms. This paper presents a new approach combining statistical analysis and advanced algorithm for signal processing, fault detection and diagnosis. Principal component analysis and artificial neural networks are employed to evaluate the signals and detect the alarm activation pattern. The dataset has been reduced by 93% and the performance of the neural network is incremented by 1000% in comparison with the performance of original dataset without filtering process.

Моделирование системы управления рысканием ветротурбины

Owing to its being an important component of renewable energy, wind energy is a kind of power generation method with the most mature, highly developed technologies and broad commercial prospects. The stable and efficient conversion of wind energy by wind turbines depends not only on the reliability of the wind power generation equipment itself, but also on the wind turbine control system, which, in turn, contributes to long-term safe and reliable operation of the wind farm fleet. It is exactly the wind turbine control system that is the main subject of this study. The key to efficient and stable operation of the entire wind energy conversion system is the control technology, which includes yaw control, pitch angle control, and maximum power point tracking control. The active yaw control system is one of the important components of a horizontal axis wind turbine's control system. To eliminate the uncertainty of wind direction influence on the turbine power output, a composite yaw control system has been checked. By using an active yaw system and maximum power point tracking system, the turbine position and its rotation speed are adjusted to enable the wind turbine to accurately track the wind direction and capture the wind energy to the fullest extent.

Black-Start Capability of DFIG Wind Turbines Through a Grid-Forming Control Based on the Rotor Flux Orientation

The increasing penetration of renewable energies in the power system is demanding new services from wind farms. In particular, system operators are concerned about system restoration after a black-out and new grid codes are under consideration that demand the participation of wind farms in the restoration process. Black start requires the wind farms to be capable of controlling voltage and frequency in an isolated grid. This paper proposes the use of a novel grid forming control for doubly fed induction generators (DFIG) for restoring the system after a black-out. The proposed grid forming control uses the rotor flux orientation principle, that allows to generate an internal electromotive force for controlling in this way the terminal voltage and frequency. Then, it is demonstrated that the rotor flux magnitude and frequency can be controlled by means of the rotor voltage applied the rotor side converter of the DFIG. The paper also proposes a wind turbine control system for balancing the power demanded by the load at the wind turbine mechanical system. Black start capability of the proposed control system has been validated through a comprehensive simulation. The simulated system consists of a wind farm with two DFIG-based wind turbines connected in parallel to a point of common coupling that supplies an induction motor through a feeder. Also, the synchronization of the isolated system to a main grid has been simulated, demonstrating the ability of the proposed control system for successfully completing the restoration process.