Wind Energy Conversion System Research Articles

A modular IGBT power stack − based and open hardware framework for small wind turbines assessment

Wind energy technologies have emerged as the predominant renewable energy source within the framework of present-day electric power systems. Their design process, aligned with foundational theories, ought to be precision-engineered and systematized to fully maximize the potential of this energy source. This study presents a platform as solution designed and built to characterize and assess Small Wind Turbines (SWT), based on free software and open hardware. Additionally, the developed methodology step-by-step guide is disclosed. The characterization is based on the use of Permanent-Magnet Synchronous Generator (PMSG) as machine widely adopted in Wind Energy Conversion System (WECS) less than 100 kW. The core theoretical background is detailed to confirm the accuracy of the parameters procedures acquisitions. Poles number, machine design constant, armature reactance, synchronous reactance, and power-dynamic characteristic related to WECS are determined. This laboratory set-up is composed of variable industrial fan, rectifier, boost converter and a bidirectional Direct-Current (DC) source as a battery emulator. All components have been assembled within the laboratory environment using commercially available elements. Low implementation cost and versatile methods determine the real input in practice of this platform. To validate the effectiveness for any SWT, a real one is tested, and every parameter proposed is calculated.

A review and comparative analysis of maximum power point tracking control algorithms for wind energy conversion systems

A review and comparative analysis of maximum power point tracking control algorithms for wind energy conversion systems

Adaptive neuro fuzzy technology to enhance PID performances within VCA for grid-connected wind system under nonlinear behaviors: FPGA hardware implementation

Wind Energy Conversion Systems (WECSs) exhibit nonlinear behavior due to internal and external disturbances, which can significantly impact the control performance. Firstly, this paper proposes a Vector Control Approach (VCA) based on Adaptive Neuro Fuzzy (ANF) of Proportional Integral Derivative (PID) controllers for a variable speed Permanent Magnet Synchronous Generator (PMSG)-based WECS connected to the grid to address these issues. The proposed ANF-PID controller combines the robustness of the fuzzy logic with the neural network's performance to ensure high accuracy, excellent tracking, and robustness against the WECS's nonlinear behavior. The neural network automates the placement of fuzzy logic membership functions. Secondly, this paper suggests a real-time hardware implementation of the VCA based on ANF-PID using a Field Programmable Gate Array (FPGA) to reduce the processing time and the WECS's sampling period. The effectiveness of the VCA based on ANF-PID controllers is validated by conducting a numerical simulation within the Matlab-Simulink using the Xilinx System Generator tool, alongside an experimental in-the-loop hardware implementation using FPGA board. Different scenarios are conducted to validate the robustness and stability of the proposed VCA based on ANF-PID control schemes, which is compared to Conventional Fuzzy PID (C-FPID) and PID controllers. The results exhibit that the VCA based on ANF-PID controllers outperforms VCA-C-FPID and VCA-PID controllers in terms of precision, tracking accuracy, and robustness against the WECS's nonlinear behavior and the PMSG parameter variations. The performances of the proposed controllers are tested under some criteria. In fact, the proposed ANF-PID controller provides a Mean Absolute Error (MAE), a Mean Squared Error (MSE) and a Root Mean Squared Error (RMSE) of 8.1911 × 10−04, 8.4181 × 10−05 and 0.0092, respectively. Compared to the C-FPID controller, the proposed controller offers an improvement gain of 98.96 %, 99.61 %, and 93.79 % of MAE, MSE, and RMSE, respectively. When compared to the PID controller, its improvement is even more significant, with a reduction of 99.9919 %, 99.9999 %, and 99.9288 % of MAE, MSE, and RMSE, respectively. In addition, the ANF-PID-based VCA utilizes hardware resources on the FPGA efficiently, requiring only 65.60 % slices LUT, 0.28 % LUTRAM, and 22.99 % FF. This makes it a more cost-effective option compared to the VCA-C-FPID controller for diverse control systems.

Comparative study between two artificial intelligence techniques (NN and SVM) applied in fault diagnosis of Wind Turbine

This paper addresses the application of artificial intelligence (AI) techniques for the classification of faults in wind turbine. Wind Energy Conversion Systems have become a focal point in the research of renewable energy sources. Reliability of wind turbine is critical to extract this maximum amount of energy from the wind. Many condition monitoring techniques that are based on steady-state analysis are being applied to wind generators. Bearing faults in this generator causes mechanical vibrations and the variations in the air gap density. The air gap flux density is modulated and currents are generated at different frequencies related to the mechanical vibrations. Characteristic bearing frequencies are associated with the physical construction of bearing and its failure mode. Classical spectral analysis using the Fourier transform was used to detect different bearing failure modes. The magnitudes of the frequencies components formed by the bearing defect are small compared to the rest of the current spectrum. This large difference in magnitude makes difficult the detection and classification of bearing faults. In this paper, we show that the utilization of different approaches of artificial intelligence such as neuronal network (NN) and support vector machines (SVM) can be discriminate different failure modes and gives a good basis for an automatic and non-invasive condition monitoring for wind turbine.

A Three-Level Neutral-Point-Clamped Converter Based Standalone Wind Energy Conversion System Controlled with a New Simplified Line-to-Line Space Vector Modulation

Wind power systems, which are currently being constructed for the electricity worldwide market, are mostly based on Doubly Fed Induction Generators (DFIGs). To control such systems, multilevel converters are increasingly preferred due to the well-known benefits they provide. This paper deals with the control of a standalone DFIG-based Wind Energy Conversion System (WECS) by using a three-level Neutral-Point-Clamped (NPC) converter. The frequency and magnitude of the stator output voltage of the DFIG are controlled and fixed at nominal values despite the variable rotor speed, ensuring a continuous AC supply for three-phase loads. This task is achieved by controlling the DFIG rotor currents via a PI controller combined with a new Simplified Direct Space Vector Modulation strategy (SDSVM), which is applied to the three-level NPC converter. This strategy is based on the use of a line-to-line three-level converter space vector diagram without using Park transformation and then simplifying it to that of a two-level converter. The performance of the proposed SDSVM technique in terms of controlling the three-level NPC-converter-based standalone WECS is demonstrated through simulation results. The whole WECS control and the SDSVM strategy are implemented on a dSPACE DS 1104 board that drives a DFIG-based wind system test bench. The obtained experimental results confirm the validity and performance in terms of control.

LVRT Enhancement of DFIG-based WECS using SVPWM-based Inverter Control

Abstract: Across many countries, wind turbine generation systems (WTGS) have been established over the past few decades. In this paper, we augment the low voltage ride-through (LVRT) enrichment facility of driving a DFIG-based wind energy conversion system (WECS) using space vector pulse width modulation (SVPWM)-based inverter control. The proposed technique employs an SVPWM-based control algorithm to regulate the voltage and frequency of the output power during grid faults, thereby enhancing the WECS's ability to remain connected to the grid and provide power. The study focuses on decreasing transient current throughout the instant of fault. Modeling and control approaches were also discussed in this study. The performance of the proposed technique is evaluated using MATLAB/Simulink simulations, and the results demonstrate that the technique effectively improves the LVRT capability of the DFIG-based WECS. Background: Due to the variation in wind speed, the power generated by wind turbines is inconsistent. The power generated and the losses in wind turbines change correspondingly with changes in wind speed. The only type of machine that can generate power at speeds below the fixed speed is the doubly-fed induction generator (DFIG). But DFIG is oversensitive to network faults, which makes the bidirectional converters and DC link capacitor fail due to high inrush current and over-voltage. Methods: The converters connected to DFIG consist of an AC-to-DC converter, a boost converter, and a space vector pulse width modulation (SVPWM)-based DC-AC converter. The performance of the SVPWM controller is analyzed during symmetrical and unsymmetrical fault conditions. Results: The anticipated control provides adequate reactive power support to the network through the time of the fault and improves voltage and current waveform. The reactive power flow is also analyzed, and the effectiveness of the proposed controller is verified using MATLAB and Simulink. Conclusion: SVPWM (Space Vector Pulse Width Modulation)-based inverter control is an effective technique for wind energy conversion systems (WECS). The use of SVPWM can provide accurate and precise control of the AC voltage generated from the DC voltage source, resulting in improved system efficiency and reduced harmonic distortion in the output waveform. : The comparative analysis of THD suggests that SVPWM is a superior technique compared to other inverter control techniques such as sine-triangle pulse width modulation (SPWM) and carrier-based pulse width modulation (CPWM). SVPWM can help to reduce the distortion in the output waveform, leading to improved system efficiency, reduced wear on the system components, and overall better performance of the WECS. Furthermore, SVPWM offers several advantages over other inverter control techniques, including better utilization of DC voltage, improved voltage control, and better utilization of switching devices. These advantages make SVPWM a valuable tool for optimizing the operation of WECS and improving the reliability and performance of renewable energy systems. The value of THD for SVPWM inverter control in WECS is 1.53 under symmetrical fault and 1.34 for unsymmetrical fault, respectively. In summary, the use of SVPWM-based inverter control for WECS is an effective way to improve the efficiency and performance of the system while reducing the distortion in the output waveform and providing adequate reactive power support. The advantages of SVPWM over other inverter control techniques make it a valuable tool for the development and optimization of renewable energy systems.

An Improved Current-Source-Converter-Based Series-Connected Wind Energy Conversion System

The passive rectifier-based current source converter (CSC) used in the series-connected wind energy conversion system features low cost, high reliability, and simple control, but suffers highly distorted generator stator currents. A new CSC-based wind energy conversion system composed of a multi-phase generator, a passive rectifier, a modular medium-frequency transformer-based converter, and a CSC, is proposed. In addition, two versions of the proposed converter are developed for low- and medium-voltage turbine systems respectively. The operation principle is presented, controls are developed, and simulations and experiments are conducted. Both converters offer excellent generator stator current harmonics performance, while also retaining the advantages of existing CSC-based converters.

Comparative evaluation of Z source / quasi Z-source direct and indirect matrix converters for PMG based WECS

The present era sees the dominance of wind energy conversion systems as a leading technology in renewable energy. Various technologies have been devised to harness wind energy, with variable speed systems emerging as particularly advantageous. Consequently, these systems are designed to operate at specified speeds using power electronic interfaces, maximizing power extraction from the wind. The integration of Permanent Magnet Generators (PMGs), directly linked to the wind turbine lacking a gearbox, allows operation at minimum speeds. To stabilize the continuously fluctuating output voltage of the PMG, power electronic converters are extensively utilized in Wind Energy Conversion Systems (WECS), ensuring a consistent voltage and frequency output. The voltage gain of Traditional matrix converters (MCs) is limited to less than 0.866. In turn, the Z-source (ZS) and discontinuous QZSDMC, as well as ZS IMCs, topologies have achieved voltage gains exceeding 0.866. However, the former provides complicated commutation issues from DMC, while the latter incorporates a Z source network in the DC link, resulting in a non-all-silicon solution. A novel continuous QZSDMC and QZSIMC are suggested, wherein a qZS network incorporates the grid-side filtering function. This design eliminates the need for an additional input filter in the proposed system. Three newly introduced topologies of ZSDMC, QZSDMC and QZSIMC are thoroughly compared across various parameters including voltage gain, current and voltage ripples, inductor current and capacitor voltage stresses, filtering capabilities, input current, and output voltage Total Harmonic Distortion (THD), finally efficiency. The paper presents their control and modulation methods to achieve the desired performance levels. Experimental comparisons validate the theoretical analysis and demonstrate the potential of the proposed QZSDMC as a promising topology.

Performance analysis of DFIG support microgrid using GA optimized restricted Boltzmann Machine algorithm

Voltage and reactive power regulation in a deregulated microgrid can be achieved by strategically placing the Static Synchronous Compensator (STATCOM) in coordination with other renewable energy sources, thus ensuring high-end stability and independent control. STATCOM plays a crucial role in effectively addressing power quality issues such as voltage fluctuation and reactive power imbalances caused by the intermittent nature of wind energy conversion systems. To successfully integrate STATCOM into the existing system, it is essential that the control system employed for STATCOM coordination aligns with the Doubly-Fed Induction Generator (DFIG) controller within the microgrid. Therefore, an efficient control algorithm is required in the microgrid, capable of coordinating with the DFIG controller while maintaining system stability. The utilization of a Genetic Algorithm (GA) in calibrating the Restricted Boltzmannn Machine (RBM) can streamline the process of determining optimal hyperparameters for specific tasks, eliminating the need for computationally intensive and time-consuming grid searches or manual tuning. This approach is particularly advantageous when dealing with large datasets within short time durations. In this research, a Simulink model comprising a DFIG-based microgrid and STATCOM has been developed to demonstrate the effectiveness of the proposed control system using RBM in managing STATCOM and facilitating microgrid operations.

DFIG in Wind Energy Applications with High Order Sliding Mode Observer-based Fault-Tolerant Control Scheme using Sea Gull Optimization

This paper describes a new method for maximizing power extraction from a wind energy conversion system (WECS) by using a doubly fed induction generator (DFIG) that operates below nominal wind speed. To maximize the collected power of a wind turbine (WTG) exposed to actuator failure, a fault-tolerant high-order sliding mode observer (HOSMO) and Seagull Optimization Algorithm with a model predictive controller (MPC) technique is proposed. Evaluate both the real state and the sensor error simultaneously using a higher-order sliding-mode observer. Active fault tolerant controllers are designed to regulate wind turbine rotor speed and power in the presence of actuator defects and uncertainty. With the growing interest in employing wind turbines (WTGs) as the primary generators of electrical energy, fault tolerance has been seen as essential to improving efficiency and reliability. This research focuses on optimal fault-tolerant pitch control, which is used to modify the pitch angle of wind turbine blades in the event of sensor, actuator, and system failures. A Seagull Optimization Algorithm (SOA) is proposed to tune controller parameters to improve the performance of WT. The proposed method has achieved 92% of power tracking performance when compared to existing method.

A Review on Crack Detection in Wind Turbine Blade

Abstract: It was observed that there is a need to reduce of maintenance and operational cost of Wind Energy conversion System. The most efficient way of reducing this cost would be to carry out Non-destructive techniques (NDT) and continuously monitor the condition of the system. This allows for early detection of the blade Cracking or damage, minimizing downtime, and maximizing productivity. The importance of condition monitoring and fault diagnosis in WECS (blades) and keeping in mind the need for future research, this paper is intended as a brief status describing different type of faults, methods of detection and future aspects

Implementation of variable frequency transformer for integration of stand alone wind energy conversion system with battery energy storage

The conventional power electronics interface used for integration of wind energy conversion system (WECS) with load produces harmonics which deteriorates the quality of power supplied. To overcome this drawback, a variable frequency transformer (VFT) has been used as a link between WECS and load. For this, first a detailed steady-state modeling of VFT has been carried out. The derived model is then used for the analysis of the steady-state performance of VFT which acts as a link between WECS with battery energy storage and load for standalone operation. For this purpose, an equivalent circuit of VFT for standalone operation is developed. A set of equations for the output voltage and power delivered by VFT is derived from its equivalent circuit. The analytical solution of these equations helps in assessing the behavior of VFT. To validate the analytical results obtained from equivalent circuit, an experimental study is also carried out. The experimental study is conducted on a 3 phase, 400 V (L-L), 50 Hz, 2.2 kW, 1440 rpm, 4 pole, wound rotor induction machine. On comparison between analytical and experimental results, it is evident that both results are in good agreement. Further, the analysis is extended for variable load under various values of wind turbine generator speed and load power factor.

Comparative study of controllers in battery energy storage system integrated with doubly fed induction generator-based wind energy conversion system for power quality improvement

This study presents a comparative analysis of controllers in a Battery Energy Storage System (BESS) integrated with a Doubly Fed Induction Generator (DFIG)-based Wind Energy Conversion System (WECS) aimed at improving power quality. The research background introduces the challenges associated with integrating renewable energy sources into the grid, emphasizing the intermittent nature of wind energy and its impact on power quality. Existing detailed problems, including voltage and frequency fluctuations, and grid instability, are outlined, highlighting the need for effective control strategies to mitigate these issues. The paper's contribution lies in evaluating and comparing different control techniques for BESS integration, including Proportional-Integral (PI) control, Fuzzy Logic (FL), and Artificial Neural Network (ANN) control. Through simulation studies conducted in MATLAB/Simulink, the effectiveness of each controller in regulating rotor current, rotor and stator power, voltage stability, state of charge (SoC) and grid synchronization is assessed. The findings provide valuable insights into the optimal controller selection for enhancing power quality in DFIG-based WECS with integrated energy storage systems, contributing to the advancement of renewable energy integration and grid stability.

Stability analysis and application of a synchronverter-based control approach to DFIG-based wind energy conversion systems

This work proposes an enhanced control approach relying on the synchronverter concept for wind energy conversion systems (WECSs) based on the doubly-fed induction generator (DFIG). It consists of incorporating a virtual filter resistor into the control loop of the synchronverter, which is associated with the grid-side converter (GSC) aiming at emulating the behavior of a synchronous generator when providing ancillary services such as frequency support. A comprehensive state-space representation is derived to demonstrate that the virtual filter resistor is essential to ensure stability. After the proper adjustment of the model, it is possible to verify the effectiveness of the synchronverter-based control applied in the IEEE 14-bus modified system employing parameters obtained from a real power plant. The results show that the application of the introduced method results in less severe frequency dips and faster transient response during frequency support even when compared with the case in which only synchronous machines are connected to the grid.

A Comparative Analysis on Proportional-Integral and Fuzzy-Logic Control Strategies for Doubly-Fed Induction Generators

This research investigates superior control methods for optimize the performance of Doubly-Fed Induction Generators in wind energy conversion systems. This proposed work, compares the well-established Proportional-Integral controller, with a Fuzzy Logic controller, known for its effectiveness in managing non-linear systems. To achieve a thorough analysis, this research develops a detailed mathematical model, specifically adopted to the DFIG system. It employs a PI controller for both the rotor-side and grid-side converters of the DFIG system. To enhance performance, a Fuzzy Logic controller is introduced to replace the PI controller, based on real-time operating conditions and gain values. Extensive simulations evaluate rigorously various performance metrics of the DFIG system under different control strategies. This analysis provides valuable insights to guide the selection of optimal control techniques, for wind energy systems using DFIGs. The analysis contributes to advancements in reliability, and efficiency for DFIG-based wind-energy systems, furthering the development of sustainable energy solutions.

Artificial neural network-based direct power control to enhance the performance of a PMSG-wind energy conversion system under real wind speed and parameter uncertainties: An experimental validation

With the increasing emphasis on embedding advanced technology into system controls, the Direct Power Control (DPC) approach has garnered considerable attention due to its simple and highly adaptable algorithm. This approach has been increasingly recognized in numerous applications. However, the variable frequency, harmonic distortion of the currents, and power ripples caused by Hysteresis controllers and switching tables decrease its effectiveness and robustness, affecting the system’s performance. For this reason, this paper proposed a new DPC based on Artificial Neural Network (ANN) approaches. In this approach, the hysteresis comparator and the switching table are substituted with ANN controllers and then applied on both sides: machine-side converter (MSC) and grid-side converter (GSC) of a Permanent Magnet Synchronous Generator based Wind Energy Conversion System (PMSG-WECS). Moreover, to make the system more efficient in varying wind conditions, this study expands the utilization of the artificial neural networks (ANN) to encompass the maximum power point tracking (MPPT) control strategy. To demonstrate the effectiveness of the proposed approach on the system behaviors, a simulation test was carried out in the Matlab/Simulink environment, using a real wind profile of a Moroccan city (Essaouira). In comparison to the classical DPC control, the simulation results showed the superior performance of the proposed ANN-DPC control in terms of reference tracking, response time, overshoot, precision, and its capacity to reduce the rate of power ripples and total harmonic distortion (THD) in the injected currents. Furthermore, a robustness test was also included in this work to check the robustness of the proposed control against parameters variation. In conclusion, the feasibility and effectiveness of the ANN-DPC control approach were confirmed through experimental validation using the dSPACE DS1104 board.

Moth Flame Algorithm to Optimize the Size and Location of Energy Storage Units in a Radial Distribution Network to mitigate Power Loss

The ideal placements and capacities for Battery Energy Storage Systems (BESS) sources in a distributed generation (DG) environment have an impact on power losses in the distribution network. Therefore, engineers are quite concerned with DG and BESS. The output from DG is, however, typically unpredictable and inconsistent. The secure and stable functioning of the power system will be impacted to varying degrees when it is connected to various sites, capabilities, and power grids. To provide a safer, more stable, more dependable, as well as more effective power grid operation, power grid planners must take the impact of capacity, type, and location into account while choosing the best BESS accessibility method. The objective is to choose bus stops with the right potential and minimal loss. This study demonstrates how to use a Moth Flame Optimization Algorithm (MFOA) to establish the appropriate battery energy storage system (BESS) sizing in a hybrid solar and wind energy conversion system (WECS) generation integrated in a radial distribution network. This research investigates the optimal capacities and allotment of the BESSs within a 33-bus and 69-bus radial network of distribution for the maximum power dissipation reduction. This research also provides a framework for carrying out conservation voltage reduction (CVR) when distributed energy resources like solar photovoltaic (PV) systems, WECS, and energy storage systems (ESSs) are connected into distribution networks. The simulation has been conducted using Matlab code and the suggested method's output is compared with Firefly Algorithm (FA), Genetic Algorithm (GA) and Ant Colony Algorithms (ACA) and evaluated against other results.

Modified Multimachine Power System Design with DFIG-WECS and Damping Controller

Rotor angle stability, which involves electromechanical oscillation damping and control, is very important in maintaining the stability of modern power grid systems. Renewable energy sources like wind energy are undergoing massive integration into modern power grid systems to meet energy demands and decarbonize power grid systems of carbon emissions from fossil fuel generators. To enable increased integration of wind renewable energy sources, precise models are needed for research and analytical purposes. Wind renewable energy is generated through a wind energy conversion system (WECS); one such conversion system is the doubly fed induction generator (DFIG) system. In this study, a precise model of a DFIG-WECS was modeled and integrated into the IEEE’s two-area Kundur power test system, which represents the available power grid system, and is also a multimachine power system using the Matlab/Simulink 2023 software. A damping controller known as the power system stabilizer (PSS), whose optimal parameters were obtained using artificial eco-system optimization (AEO), was also incorporated into the integrated power grid system to control and damp electromechanical oscillations. The results showed that the PSS damping controller effectively damped electromechanical oscillations in the integrated power grid system.

A new passive‐based active disturbance rejection control for PMSG system with saturation constraints

AbstractThe disturbance in wind energy conversion system has a serious negative impact on the maximum power tracking performance of the system, and the saturation constraint problem also seriously restricts the stability of the control system. Therefore, a novel model compensation passive‐based active disturbance rejection control strategy is proposed to suppress the disturbance and saturation constraints, thus improving the tracking performance of the permanent magnet synchronous generator system in this paper. Taking advantage of the fact that active disturbance rejection control technology can estimate and compensate for the disturbances of the system in real time, a model compensation active disturbance rejection control method is proposed to make the system more robust to the changes in its own parameters and external disturbance. At the same time, the control input signal of the controller is given. A model compensation passive‐based active disturbance rejection controller is designed by using the passive control method, and the nonlinear sector method is introduced to solve the saturation constraint problem of the system. Simulation results show that the control strategy can effectively reduce overshoot, improve the system's response speed, have a good anti‐interference ability, and effectively suppress the influence of saturation constraints on the system.

Control of DFIG-based microgrid and seamless transition from stator connected and disconnected modes

This study aims to ameliorate the contribution capability of doubly-fed induction generator (DFIG) to participate in standalone microgrid operation. The islanded microgrid consists of a solar photovoltaic array for solar energy conversion and battery energy storage in addition to DFIG-based wind energy conversion system. Using a simplified control approach, the study describes multi-mode operation of a DFIG-based AC/DC microgrid using a stator-side solid-state transition switch (SSTS). Using SSTS operation, the DFIG stator can be seamlessly disconnected and reconnected from the point of common coupling without interrupting power to the loads in the microgrid. Additionally, non-ideal AC loads can be handled efficiently without the need for computationally exhaustive approaches to enhance stator voltages and currents.