Wind Turbine Generator Research Articles

Structure failure and strength evaluation of honeycomb-based sandwich composites under variable hydro-thermal-mechanical load

The high-strength and lightweight sandwich structures have broad application prospect in aerospace, wind turbine generator, traffic and civil engineering. The sandwich structures usually service with severe environment and complicated mechanical load, structure failure and strength prediction are crucial issues. Under time-varying and optional position hydro-thermal–mechanical loading, this paper systematically analyzes strength failure, buckling and delamination of a sandwich beam with carbon fiber-reinforced polymer face sheet and aluminum honeycomb core. Effects of elastic boundary conditions, hydrothermal stress, configuration of honeycomb cell and thickness of face sheet on failure pattern and critical failure loading are evaluated. The theoretical deformation model is verified by performing a bending experiment of cantilever beam. For the honeycomb core with small re-entrant angle and shot horizontal cell wall, the sandwich cantilever beam occurs strength failure of face sheet and delamination is happened in simply supported beam. With increase of re-entrant angle and cell wall length, buckling of horizontal cell wall becomes the primary failure pattern of sandwich beam. With thickness increase of face sheet, the failure pattern switches from face sheet’s strength failure to delamination. The critical load for delamination decreases to a volley value and then increases with thickness of face sheet.

Adaptive Inertial Control for Wind Turbine Generators in Fast Frequency Response Based on the Power Reduction Period Assessment

Adaptive Inertial Control for Wind Turbine Generators in Fast Frequency Response Based on the Power Reduction Period Assessment

Research on harmonic impedance characteristics of low- and medium-frequency grid-forming wind turbine generators

Research on harmonic impedance characteristics of low- and medium-frequency grid-forming wind turbine generators

Inertia Support Capability Evaluation for Wind Turbine Generators Based on Symmetrical Operation

With the increasing integration of new energy into the grid, the level of system inertia has been significantly reduced, posing a severe challenge to frequency stability. Consequently, there is an urgent need for wind turbine generators (WTGs) to actively provide inertia support through virtual inertia control. Assessing the inertia support capability of WTGs reasonably and setting appropriate controller parameters based on this assessment is a topic worthy of discussion. As WTGs’ characteristics are mostly ignored in the evaluation of inertia support capability for WTGs, an evaluation method based on symmetrical operation is proposed. The proposed method considers the impact of real inertia and aerodynamic characteristics, thereby helping to determine reasonable virtual inertia coefficients and de-loading reserve capacity for WTGs. With the proposed method, it can be determined that large WTGs can provide inertia support capabilities close to those of synchronous generators to the grid without exceeding a 0.1% reduction in reserve capacity during de-loading operation.

Fractional order control of Wind Energy Conversion System based on DFIG

The paper deals with the elaboration of a robust and efficient decoupled active and reactive powers control algorithm of double-fed induction generator (DFIG) using fractional order control based on proportional and integral controllers. First, the models of wind turbine and electrical generator are established, as well as a decoupled active and reactive powers control of DFIG. Second, the used fractional order controllers are designed using an analytical design method based on frequency domain specifications, namely phase margin, robustness to gain variations and gain limitation at the crossover frequency. Third, to evaluate the fractional order controller control performances, simulation results are presented and discussed for all the operating region of the WECS. Then, simulation results are presented and interpreted considering a variable wind speed in order to reach all the operating regions of the WECS. Finally, a conclusion is given in the light of the obtained results.

Simulation of Doubly Fed Induction generator (DFIG) for Steady state analysis when connected to a wind farm for power system stability

In this paper, a 2MW variable speed, pitch-regulated Doubly-fed Induction Generator (DFIG) with a speed range of 800-2000 rpm was studied for steady-state analysis. The DFIG was modelled in the Matlab/Simulink environment. The rotor-side converter utilized closed-loop stator flux-oriented vector control for managing the DFIG model. This method allows for rapid control and experimenting of grid-connected, variable speed DFIG wind turbines to examine their steady-state and energetic characteristics beneath ordinary and disturbed wind conditions when connected to a wind farm. The steady-state behavior of the wind turbine generator was derived at two different magnetizing levels: one with the reactive power of the stator equal to zero (Qs = 0), and the other with the direct current of the rotor equal to zero (Idr = 0). Simulation results show that the machine has higher efficiency when magnetized through the stator as compared with magnetization of the machine through the rotor. To come out with the DFIG transitory stability simulation results traditional controllers' for active and reactive power were compared with an adaptive adaptive tracking, self-tuned feedforward proportional integral regulating model for peak performance. Additionally, stability and instability were studied by solving the Swing equation using the Runge-Kutta method of order four. In a steady-state condition for the generator, the acceleration torque (Ta) reaches zero, which signifies that the mechanical torque (Tm) matches the electrical torque (Te). In the stability investigation, Tm is assumed to be constant. The findings provide valuable insights into the control strategies required for enhancing the reliability and efficiency of wind turbines in variable wind conditions.

Hydraulic fault detection of wind turbine generators using artificial neural networks

In the current context where fossil resources are diminishing globally, and carbon emissions are increasing daily, the importance of green energy, particularly wind energy, is growing significantly. The increasing of wind turbines will not only reduce the carbon footprint but also decrease dependence on external resources. To increase the installed capacity of wind turbines, it is crucial to reduce not only installation costs but also operational costs. The largest proportion of operational costs is service, and maintenance costs. One of the most critical approaches to reducing service, and maintenance costs is preventive maintenance activities. The objective of preventive maintenance activities is to minimize or ideally eliminate production losses through scheduled turbine shutdowns before failures occur. In this study, artificial neural network-based algorithms that predict potential hydraulic failures during the operational period were utilized. For this purpose, data from the turbine SCADA system over a period of two years, considering the equipment, and sensors connected to hydraulic systems, were compiled. The study was conducted using the WEKA program, comparing Multilayer Perceptron (MLP), Radial Basis Function Classifier (RBF Classifier), SMOreg (Support Vector Machines for Regression) algorithms. Result of the study, the MLP algorithm was applied with a percentage split of 66% for training, and 33% for testing, achieving a prediction accuracy of 96.32%

Modeling, Control Study, and Power Management Strategy of a Hybrid Grid-Connected AC/DC Microgrid with High Integration of Renewable Energies and Green Hydrogen Sources

Abstract This first quarter of the 21st century is increasingly marked by population growth, digital and industrial de- velopments, growing need for electricity supply, and climate change. All this, to name just a few, have made the establishment of a stable, flexible, controlled, well-designed, extensive and clean power system a necessity. Conse- quently, distributed microgrid generation based on alternative/renewable energies and/or low-carbon technologies has emerged. In this paper, we study the modeling, the control, and the power management strategy of a grid-connected hybrid Alternating/Direct Current (AC/DC) microgrid based on a wind turbine generation system using doubly fed induction generator, a photovoltaic generation system, and storage elements including hydrogen storage system and batteries. Adequate modeling is described, and the overall system monitoring is presented and applied to manage appropriate power sharing and to control active and reactive powers, in order to match load and weather fluctuation behaviour. Simulations are carried out using MATLAB/Simulink simulation tool. Simulations reveal convenient re- sults in terms of the bidirectional interlinking converter capabilities regarding power balance establishment between the two subgrids, reactive power compensation to ensure a unity power factor, and DC-bus voltage regulation at 1200 V. In addition, the primary and secondary controls are approved for each distributed generation of the studied system to attain the assigned power references, regardless of whether the subgrid is heavily or lightly loaded throughout the four considered case studies, showing satisfactory tracking and interacting performances, and thus stimulating a stable system implementation.

Control strategy of the novel stator free speed regulating wind turbine generation system.

Building a high-proportion renewable energy power system is a key measure to address the challenges of the energy revolution and climate change. However, current high-proportion renewable energy systems face issues of frequency instability and voltage fluctuations. To address these challenges, this paper proposes a novel topology for a stator free speed regulating wind turbine generation system. The stator free speed regulating machine connects a gearbox and a synchronous generator, forming a flexible drive chain that increases system inertia and enhances frequency stability in high-proportion renewable energy power systems. The synchronous generator at the end of the drive chain can be directly connected to the grid without the converter, thanks to the speed regulation provided by the stator free speed regulating machine, thus avoiding harmonic pollution caused by power electronic devices in traditional wind turbines, enhancing the reactive power support capability, and improving voltage stability in high-proportion renewable energy systems. Given that the proposed stator free speed regulating machine consists solely of a rotating inner and outer rotor without a stator, traditional motor control strategies are not applicable. Therefore, this paper focuses on developing control strategies for the stator free speed regulating machine, employing a dual closed-loop PI control strategy with an outer loop for speed and an inner loop for current, based on flux orientation of the outer rotor. Simulation experiments will validate the feasibility of the proposed stator free speed regulating wind turbine generation system topology and the effectiveness of the control strategy.

Comparative analysis of single-machine equivalent methods for heterogeneous PMSG-based wind farm with the VSC-HVDC system

This paper presents a comparative study of four single-machine equivalent methods used to simplify the analysis of small-signal stability (SSS) in grid-connected wind farms composed of multiple wind turbine generators (WTGs), particularly focusing on heterogeneous permanent magnet synchronous generator (PMSG)-based wind farms with a VSC-HVDC system. The four methods compared are (1) the dynamic aggregation method, (2) the average power or average control parameter method, (3) the weighted average method, and (4) the covering theorem method. The comparative analysis highlights the connections and differences among those four methods that help to gain a better understanding of their strengths and limitations as follows: (1) When the dynamic characteristics of individual PMSGs are different, the dynamic aggregation method may result in errors in assessing system SSS. (2) The average power and weighted average methods are accurate in assessing the system's SSS when a linear relationship exists between the system's oscillation modes and the PMSG output or control parameters. However, both methods may give erroneous SSS assessments when this linearity does not hold. (3) The weighted average method can accurately assess SSS when wind speeds differ across PMSGs, while the average wind speed method produces errors. (4) The covering theorem method is found to be conservative in SSS assessment. Finally, the methods are validated through simulations on two PMSG-based wind farm topologies connected to the grid with a VSC-HVDC system.

MPPT controller design and comparison of selected site Cox’s Bazar

Wind energy is a popular green source of energy. Like other countries, Bangladesh is also in a process of incorporating wind turbine generator (WTG) into its existing power system. Out of several locations, Cox’s Bazar has the great potential to adopt WTG. The location has every suitability to be selected for offshore WTG farm. From technical perspective, power coefficient plays a significant role in determining the power output. Against variables, maximum power coefficient (Cp) is desired to extract the maximum power from the system. Tip speed ratio (TSR) and pitch angle are the common parameters to be controlled for maximum power point tracking (MPPT). Conventionally, the Proportional - Integral - Derivative (PID) controller is used but they have their limitations against high nonlinearity caused by wind turbine aerodynamics. This paper proposes three types of controllers: Proportional controller (PI), artificial neural network (ANN), and fuzzy logic controllers. The controller is applied to both TSR and pitch angle control. Pitch angle is controlled to avoid the extreme wind gusts. All the simulation works are carried out in MATLAB and Simulink. This paper also analyzes the technical feasibility of the Cox’s Bazar location for offshore WTG.

Fault diagnosis for wind turbine generators based on Model-Agnostic Meta-Learning: A few-shot learning method

Fault diagnosis for wind turbine generators based on Model-Agnostic Meta-Learning: A few-shot learning method

Evaluation of reliability and resilience in wind integrated power systems using 80 meter mast measurements

Renewable energy sources, especially wind turbine generators, are increasingly considered viable alternatives to conventional electric power generation due to their sustainability and positive environmental impact. The rising penetration of wind power highlights the importance of developing widely applicable methods to evaluate the concrete benefits of incorporating wind turbines into traditional power systems. This work proposes an approach for assessing the reliability and resilience of power systems incorporating wind power. Evaluating the impact of wind energy generation on system reliability involves analyzing metrics such as Loss of Load Expectation (LOLE) and Expected Energy Not Supplied (EENS). Additionally, a conceptual framework is developed which is aimed at enhancing the evaluation of power system resilience, when subjected to severe wind events. To evaluate the impact of wind storms on network resilience, a Monte Carlo Optimal Power Flow approach is utilized. The Average Energy Not Supplied (AENS) is used as the resilience metric and is computed for different rated speeds of wind turbines. The proposed methods for evaluating the reliability and resilience of the power systems are tested using the IEEE-RTS 24 bus system. Real-time wind resource data measured at an 80-meters mast at Paradeep location in the Odisha state on the east coast of India are used to evaluate the indices.

Two-stage optimization strategy for the active distribution network considering source-load uncertainty

This study aims to advance the development of the active distribution network (ADN) by optimizing resource allocation across different stages to enhance overall system performance and economic benefits. First, an ADN optimization model is constructed based on a two-stage robust optimization approach. The first stage focuses on determining optimal decision variables within the uncertainty set, while the second stage adjusts control variables based on the initial stage decisions. This model effectively addresses source-load uncertainties while preserving the flexibility and adaptability of decision-making solutions. Additionally, this study explores uncertainty models that incorporate correlation factors. The IEEE33-node model is employed to validate the effectiveness and superiority of the proposed optimization strategy through numerical simulations. Simulation results demonstrate that Model 3 comprehensively accounts for photovoltaic and wind turbine generator planning by optimizing their capacity configurations, leading to a 23% increase in distributed generation (DG) penetration. During high-load periods (e.g., 13:00 and 16:00), DG output reaches 47% and 50% of the demand load, underscoring the critical role of DG in supporting the power grid during peak hours. Overall, the proposed two-stage optimization strategy considers source-load uncertainties, significantly reducing economic costs, enhancing DG output, and improving overall system performance. In scenarios with correlated uncertainties, the optimized results exhibit greater accuracy and reliability, providing robust support for the planning and operation of practical distribution networks.

Optimal battery management in PV + WT micro-grid using MSMA on fuzzy-PID controller: a real-time study

In modern energy systems, managing energy within a microgrid (MG) poses significant challenges due to the unpredictable nature of renewable energy sources. This article introduces a novel approach for optimal battery management in a photovoltaic–wind microgrid using a Modified Slime Mould Algorithm (MSMA) combined with a fuzzy-PID controller. The microgrid comprises a wind turbine (WT) generator, solar photovoltaic (PV) generator, and a battery energy storage system (BESS). The BESS plays a crucial role in meeting high power demand during outages, while the fuzzy-PID controller ensures accurate prediction of the battery’s state of charge (SOC). The proposed method’s performance is evaluated by comparing the MSMA-based fuzzy-PID controller with a PSO-based fuzzy-PID controller to establish its effectiveness. The optimal energy management of the BESS in the microgrid is achieved by fine-tuning the fuzzy-PID controller using the MSMA algorithm. Simulation results demonstrate that the battery management system (BMS) effectively optimizes charging and discharging based on renewable energy availability and load demand. The fuzzy-PID controller adjusts battery operation by minimizing the error between the desired and actual battery voltage. Performance validation has been conducted in RTS-lab using five distinct load scenarios—45 kW, 35 kW, 75 kW, 4.5 kW, and 12.5 kW, which confirming the effectiveness of the proposed control strategy for energy management.

Fault detection of key parts of wind turbine based on BP neural network combination prediction model

A BP neural network incorporated regression forecast technique based upon fragment swarm optimization (PSO) is proposed to design the state of crucial components of wind turbine so regarding realize mistake identification and detection. Firstly, specification recognition is carried out on the collection and tracking information of the system, and parameters connected to fault detection are extracted. Then, the residual optimization issue is made use of to establish the forecast model of nonlinear state evaluation and semantic network combination, and the gearbox temperature level or generator bearing are input as criteria right into the semantic network combination model and single model specifically, and the precision of the design is mirrored by the examination index. Lastly, BP design and PSO-BP combined forecast model are developed respectively by using the actual operation data of wind ranch SCADA, and the mistake state is evaluated according to whether the anticipated residual exceeds the set threshold, so regarding keep an eye on the temperature level of wind turbine transmission and generator bearing. By contrasting the data videotaped prior to and after the failing and making the information prediction analysis, the speculative results show that the forecast model established in this paper is viable for the device element fault detection.

The Effect of Local and Interarea Oscillations of Wind Turbine Generators Based on Permanent Magnet Synchronous Generators Connected to a Power System

The Effect of Local and Interarea Oscillations of Wind Turbine Generators Based on Permanent Magnet Synchronous Generators Connected to a Power System

Grid-following and grid-forming control modes of the rotor and grid sides converters for seamless and universal operation of the hybrid DFIG-wind/battery energy storage system in grid-connected and stand-alone conditions

The system examined in this paper is a hybrid doubly-fed induction generator wind-turbine (DFIG-WT) combined with a battery energy storage system (BESS). It operates in both stand-alone and grid-connected modes, with the capability for seamless transitions between these states, and manages the state of charge (SOC) of the battery under all conditions. In this paper, by modifying control structures of the rotor-side and grid-side converters (RSC and GSC), the RSC is controlled in the grid-following (GFL) mode and the GSC in the grid-forming mode using the virtual synchronous generator technique. The proposed control scheme with detailed considerations for both the RSC and GSC simultaneously addresses the following aspects: (a) seamless operation in both grid-connected and stand-alone conditions, (b) synchronization and smooth connection of the DFIG during initial moments of grid-connection without using a phase-locked loop (PLL), (c) enabling the converters control systems to allow the grid-connected DFIG to operate not only in MPPT mode but also in power dispatch mode based on the power grid requirements, and (d) SOC adjustment of the battery in both grid-connected and islanded modes. In the grid-connected state, the battery SOC is managed by the GSC, and for SOC < 90 %, the battery is charged by the GSC according to the SOC level, and for SOC > 95 %, the GSC limits the SOC below the upper limit. In the stand-alone state, the SOC upper limits are mainly managed by the RSC, and if the SOC exceeds the value of 85 %, the RSC works in the power curtailment mode and reduces the stator power.

Research and Development of a Large-Scale Axial-Flux Generator for Hydrokinetic Power System

The study demonstrates an application of actual technologies and tools for the development of an axial-flux electricity generator. The specifics of its application—a run-of-river sited power station—predefine some of the design parameters that are close to a wind turbine generator. An extensive study of available solutions is used as a starting point for further concept development. The study aims to provide a viable solution for a large-scale electrical machine. A step-based methodology is defined for concept parameters’ assessment and a feasibility study. It demonstrates the advantages of virtual prototyping when assessing various design parameters such as air gaps, coil thickness, and the number of rotor disks. Several simulations over different virtual prototypes provide sufficient information to elaborate an improved design concept. The major result is a ready-for-detailed design concept, with defined major parameters and studied work behavior for a specific, large structure of an electrical machine. Another important result is the presentation of the application of virtual prototyping in the assessment of large structures, for which physical prototyping is an expensive and time-consuming approach. The application of virtual prototyping at a very early product development stage is an effective way to undertake efficient solutions involving the concept of the product.

Finite element based micromagnetic simulations of heterogeneous magnetic microstructures

AbstractMagnetic materials play a crucial role in our everyday lives. As permanent magnets, they are core components in electric motors such as generators for wind turbines, or, as magnetocaloric magnets, they have the potential to change the cooling technology of tomorrow. All of this makes these materials key contributors to “green” energy conversion technology. Accordingly, pushing the development of these materials with a special focus on the performance, efficiency, and harmlessness of the material components contained for humans and the environment is of crucial importance. This work deals with the finite element‐based simulations within the framework of the micromagnetic theory to numerically support the quest of characterizing novel magnetic materials. The main focus remains on the numerical modeling of permanent magnetic polycrystalline materials and the influence of grain boundaries on the effective magnetization. For this purpose, large‐scale simulations of permanent magnetic neodymium‐iron‐boron () samples are carried out and the influence of different mesh sizes on the effective magnetization behavior is investigated.