Wind Turbine Generator Research Articles

Sustainable Design of Onshore Wind Turbine Foundations

In recent times, wind power has emerged as a prominent contributor to electricity production. Minimizing the costs and maximizing sustainability of wind energy is required to improve its competitiveness against other non-renewable energy sources. This communication offers a practical approach to assess the sustainability of wind turbine generator foundations from a 3-dimensional holistic point of view. Specifically, the main goal of this study is to analyse the life cycle impacts of one shallow foundation design comparing three different concrete alternatives: conventional concrete, concrete with 66-80% of blast furnace slags and concrete with 20% fly ash, and then to apply a Multi-Criteria Decision-Making model based on TOPSIS method to evaluate and compare the resulting sustainability of each alternative considered. The study results in a methodology for quantifying sustainability rather than simply qualifying it. Therefore, this methodology can be employed for design optimization, such as geometry and materials, with a sustainable perspective in mind. Specifically in this study, concrete with blast furnace slags emerges as the top-ranked sustainable alternative, followed by conventional concrete in second place, and fly ash option in third position.

Identification method of all-operating-point admittance model for wind farms considering frequency-coupling characteristics

Admittance identification is an effective tool to solve the issue of black-box admittance modeling in wind farms. However, due to the large operating range of wind farms, it is difficult to accurately identify the admittance model of wind farms under all operating conditions, which limits the research on wideband oscillation caused by the interaction between wind farms and the power grid. This paper analyses the characteristics of the frequency-coupling admittance for wind farms. It is found that the power-sharing ratio of wind turbine generators (WTGs) affects the admittance characteristic of the wind farm, which leads to a huge number of operating points for the wind farm. The all-operating-point (AOP) admittance model of wind farms considering frequency-coupling characteristics is hard to directly identify. Aiming for this problem, this paper proposes to first identify the AOP-admittance model for WTGs. Then, based on the operating points of each WTG and the network structure, the AOP-admittance model of the wind farm is obtained via the admittance aggregation and model reduction method. This proposed method solves the problem of black-box admittance modeling and addresses the problem of dimension disaster in admittance modeling for wind farms. The identified model of the wind farm can be used to accurately assess the stability of the wind power integration system under various operating conditions. Finally, the effectiveness of the proposed method is verified through the admittance measurement and stability analysis of the wind farm.

Classification of Highly Imbalanced Supervisory Control and Data Acquisition Data for Fault Detection of Wind Turbine Generators

It is common knowledge that wind energy is a crucial, strategic component of the mix needed to create a green economy. In this regard, optimizing the operations and maintenance (O&M) of wind turbines (WTs) is key, as it will serve to reduce the levelized cost of electricity (LCOE) of wind energy. Since most modern WTs are equipped with a Supervisory Control and Data Acquisition (SCADA) system for remote monitoring and control, condition-based maintenance using SCADA data is considered a promising solution, although certain drawbacks still exist. Typically, large amounts of normal-operating SCADA data are generated against small amounts of fault-related data. In this study, we use high-frequency SCADA data from an operating WT with a significant imbalance between normal and fault classes. We implement several resampling techniques to address this challenge and generate synthetic generator fault data. In addition, several machine learning (ML) algorithms are proposed for processing the resampled data and WT generator fault classification. Experimental results show that ADASYN + Random Forest obtained the best performance, providing promising results toward wind farm O&M optimization.

Performance Analysis of Photovoltaic and Wind Turbine Grid-Connected Systems under LVRT Conditions

The integration of grid-connected renewable energy systems has gained significant attention and introduces several challenges and considerations. One of these challenges is ensuring the reliable and stable operation of these systems under various grid conditions. For example, faults at the grid could lead problems such as DC-link over-voltage and AC over-current that may cause disconnection or damage to inverter. This paper presents a comprehensive analysis of the performance of photovoltaic (PV) and doubly-fed induction generator (DFIG) wind turbine grid-connected systems under low voltage ride-through (LVRT) conditions. The study aims to investigate their behavior, and stability during LVRT events and provide insights for enhancing their grid integration capabilities. The PV and DFIG systems are modelled and simulated using MATLAB Simulink under three difference conditions, with and without using reactive current injection and DC chopper circuit. Various performance parameters, including grid voltage, grid current, DC-link voltage, active power, and reactive power, are analyzed to assess the system's behavior and compare their responses. The principal results reveal distinct performance characteristics of the PV and DFIG systems. The PV system shows higher overshoot currents, over-voltage, and significant drops in active power during fault occurrences, while the DFIG system exhibits lower overshoot currents and better stability in the DC-link voltage. Reactive power responses differ between the systems, with the PV system demonstrating a higher capability for support. The implementation of DC chopper shows more effective in the reduction of DC-link voltage and overshoot grid current in the PV system compared to the DFIG system.

Torsional and lateral vibration analysis of wind turbine generator bearing outer ring fault considering unbalanced magnetic pull

Rolling bearings play a critical role in wind turbine generators, operating continuously in an electromagnetic excitation environment. Their fault vibration characteristics are affected by unbalanced magnetic pull (UMP), which has received little attention in previous studies. Moreover, torsional vibration can provide advantages in bearing fault diagnosis, since it has a good signal-to-noise ratio (SNR) and it can be easily measured by the encoder. However, torsional vibration is rarely considered in the existing model of wind turbine generator. Accordingly, this paper proposes a dynamic model with 8 degrees of freedom to analyze the bearing outer ring fault characteristics of wind turbine generator under the influence of UMP, while also taking into account the torsional vibration in the model. The validity of the model is verified through experiments conducted on a test rig. The results displays modulation of the ball pass frequency outer (BPFO) harmonics with both UMP frequency and rotation frequency in lateral vibration, and this phenomenon can also be observed in instantaneous angular speed (IAS) and instantaneous angular acceleration (IAA) signals that represent torsional vibration. Besides, the lateral vibration spectrum reveals two distinct resonance bands, and simulation analysis suggested that the rotor and bearings give rise to low-frequency and high-frequency resonance, respectively. This study provides a reference for bearing faults diagnosis in wind turbine generator.

Life cycle environmental analysis of offshore wind power: A case study of the large-scale offshore wind farm in China

China's decarbonization is indispensable for the large-scale utilization of renewable energy. In this process, the development of offshore wind energy has become an important support, because in the eastern region of China, especially the coastal areas, there's the most load requirements but limited onshore renewable resources. Under the goals of both carbon neutral and sustainable development, however, there's still a research gap in evaluating the environmental impacts of large-scale offshore wind plants in China. In this study, the research performed a comprehensive process-based life cycle environmental analysis of a large-scale (400 MW) offshore wind farm with large wind turbine units (5 MW) in China. Global Warming Potential is 25.73 g CO2-eq/kWh and greenhouse gas payback time is calculated as 12.05 months. Fossil fuel consumption amounts to 0.31 MJ/kWh with an energy payback period of 25.56 months. Material resources and ecotoxicity to freshwater need more attention with the values of 1.68 CTUe/kWh and 3.32 10−6 kg Sb-eq/kWh, respectively. The manufacturing stage contributes most to all the impacts examined. The disposal and recycling process shows significant environmental benefits for most impacts but exerts burdens on the particulate matter. Focusing on Global Warming Potential, the wind turbine generation set has the highest effect, among which the blades contribute 73.2% of it. Further, the evolution of electricity and heating mix of China and use of biomass-based precursors could decrease 57% of the blades' greenhouse gas emissions in 2050. This study could provide guidance on the sustainable design and policy-making of offshore wind farms.

A consecutive power dispatch in wind farms to mitigate secondary frequency dips

With the rapid increase of wind energy integrated into power systems, wind turbine generators (WTGs) are required to provide frequency support to maintain the system frequency stability. However, the frequency regulation is achieved by employing temporary energy reserves from WTGs at the initial stage of a disturbance. Therefore, a second frequency dip (SFD) may occur, if no other energy reserve is available to compensate the power deficiency as WTGs have to recover their operating points and rotor speeds back to the initial operating points. To deal with this problem, this paper proposes a consecutive power dispatch scheme to reduce the SFD and prevent WTGs from over-deceleration. All WTGs are divided into two groups with in a wind farm: Group 1 (G1) WTGs operating at maximum power point tracking (MPPT), Group 2 (G2) WTGs operating at deloading power. If a frequency contingency occurs, the proposed scheme aims to release an amount of kinetic energy (KE) stored in the rotating masses of G1 WTGs to improve the frequency nadir (FN). Following this, energy reserves are released from G2 WTGs to compensate the power shortage during the period when G1 WTGs rotor speeds have to be recovered. The simulation results show that the scheme causes a small SFD while improving the first FN and preventing the rotor from over-decelerations in various wind conditions, contingency sizes, and wind penetration levels.

The Analysis of Sub-Synchronous Resonance in a Wind Farm for a Doubly-Fed Induction Generator Using Modern Analytical Method

The occurrence of Sub-Synchronous Resonance (SSR) phenomena can be attributed to the interaction that takes place between wind turbine generators and series-compensated transmission lines. The Doubly-Fed Induction Generator (DFIG) is widely recognized as a prevalent generator form employed in wind energy conversion systems. The present paper commences with an extensive exposition on modal analysis techniques employed in a series of compensated wind farms featuring Doubly Fed Induction Generators (DFIGs). The system model encompasses various components, including the aerodynamics of a wind turbine, an induction generator characterized by a sixth-order model, a second-order two-mass shaft system, a series compensated transmission line described by a fourth-order model, controllers for the Rotor-Side Converter (RSC) and the Grid-Side Converter (GSC) represented by an eighth-order model, and a first-order DC-link model. The technique of eigenvalue-based SSR analysis is extensively utilized in various academic and research domains. The eigenvalue technique depends on the initial conditions of state variables to yield an accurate outcome. The non-iterative approach, previously employed for the computation of initial values of the state variables, has exhibited issues with convergence, lack of accuracy, and excessive computational time. The comparative study evaluates the time-domain simulation outcomes under different wind speeds and compensation levels, along side the eigenvalue analysis conducted using both the suggested and non-iterative methods. This comparative analysis is conducted to illustrate the proposed approach efficacy and precision. The results indicate that the eigenvalue analysis conducted using the proposed technique exhibits more accuracy, as it aligns with the findings of the simulations across all of the investigated instances. The process of validation is executed with the MATLAB program. Within the context of the investigation, it has been found that increasing compensation levels while simultaneously decreasing wind speed leads to system instability. Therefore, modifying the compensation level by the current wind speed is advisable.

Quantifying the impact of modeling fidelity on different substructure concepts for floating offshore wind turbines – Part 1: Validation of the hydrodynamic module QBlade-Ocean

Abstract. To realize the projected increase in worldwide demand for floating offshore wind, numerical simulation tools must capture the relevant physics with a high level of detail while being numerically efficient. This allows engineers to have better designs based on more accurate predictions of the design driving loads, potentially enabling an economic breakthrough. The existing generation of offshore wind turbines is reaching a juncture, where traditional approaches, such as the blade element momentum theory, are becoming inadequate due to the increasing occurrence of substantial blade deflections. QBlade is a tool that includes a higher-fidelity aerodynamic model based on lifting-line theory, capable of accurately modeling such scenarios. In order to enable the simulation of offshore conditions in QBlade and to make use of this aerodynamic capability for novel offshore wind turbine designs, a hydrodynamic module called QBlade-Ocean was developed. In the present work, this module is validated and verified with two experimental campaigns and two state-of-the-art simulation frameworks on three distinct floating offshore wind turbine concepts. The results confirm the implementation work and fully verify QBlade as a tool to be applied in offshore wind turbine simulations. Moreover, a method aimed to improve the prediction of non-linear motions and loads under irregular wave excitation is analyzed in various conditions. This method results in a significant improvement in the surge and pitch degrees of freedom in irregular wave cases. Once wind loads are included, the method remains accurate in the pitch degree of freedom, while the improvements in the surge degree of freedom are reduced. A code-to-code comparison with the industry-designed Hexafloat concept highlights the coupled interactions on floating turbines that can lead to large differences in motion and load responses in otherwise identically behaving simulation frameworks.

A Stiffness Approach for Coupling Structural and Magnetic Models for the Sustainable Design, Optimisation and Real-Time Structural Integrity Assessment of Radial Flux Permanent Magnet Generators for Direct-Drive Wind Turbines

The mass of a direct-drive generator is often defined by the requirements for structural stiffness to meet the magnetic stiffness between the rotor and stator surfaces. This paper analyses this magnetic stiffness and estimates the structural stiffness of direct-drive generators for different modes of deflection. The magnetic stiffness modelling is based on an analytical model of the airgap closing forces. The final models are verified using finite element analysis and developed for both permanent magnet and wound rotor generators. It shows that wound rotor machines have higher stiffness requirements than permanent magnet machines. The structural stiffness of the generator rotor and stator is evaluated for different modes by applying spatially varying forces and finding the associated deflections. Structural stiffnesses for the rotor, stator and bearing are then combined. Finally, the magnetic and structural stiffnesses are combined and a stiffness margin can be found. This method is applied to a relatively stiff and a relatively compliant set of generator structures in a case study. The analytical model presented in this paper is useful for structural optimisation purposes or as part of an online structural health monitoring system as it could assess the integrity of the machines in real time.

Injection-Space Security Region for Sub/Super-Synchronous Oscillation in Wind Power Integrated Power Systems

The complex interactions between converter-based wind turbine generators (WTGs) and power grid have brought new sub/super-synchronous oscillation (SSO) issues. The stability of such oscillation is closely related to system operating conditions. Thus it is necessary to identify SSO stability under various possible operating conditions. To achieve this, this paper first proposes the concept of security region (SR) for SSO, which is composed of all operating points in the injection space to ensure the stability of SSO modes. Then an operating condition dependent impedance model-based oscillation stability analysis method is developed to evaluate the SSO stability. Next, the predictor-corrector technique is adopted to build the SR boundary using the correlation among adjacent boundary points. The boundary is further approximated via hyperplane fitting according to its topological property. Finally, the proposed method is applied on a practical wind power system suffering SSO to construct the SR. Its effectiveness as well as advantages over traditional point-wise based method are demonstrated with random experiment and EMT simulation.

A novel structure of magnetic geared generator in dual-rotor wind turbine

Variable-speed constant-frequency generating systems are commonly employed in wind turbines to enhance efficiency and minimize losses. Additionally, the utilization of dual-rotor wind turbines enables the capture of a greater amount of wind energy, leading to a significant increase in efficiency. Traditionally, dual-rotor wind turbines are managed by a full-scale power converter, and the rotor current is transmitted through brushes, which substantially raises the system's cost. To address these challenges, this study introduces a novel configuration that enables power control with a smaller power converter. In contrast to conventional dual-rotor wind turbines that generate power using both rotors, the proposed structure designates one rotor as a system controller. Apart from these benefits, the proposed structure greatly enhances conversion performance by notably improving the power factor. A comparison with existing configurations described in literature is conducted to demonstrate the superiority of the proposed structure.

Moment-Based Analysis of Onshore Wind Turbine Generator Foundation–Soil Response

Moment-Based Analysis of Onshore Wind Turbine Generator Foundation–Soil Response

A Dynamic Equivalent Method for PMSG-WTG Based Wind Farms Considering Wind Speeds and Fault Severities

The dynamic security assessment of power systems needs to scan contingencies in a preselected set through time-domain simulations. With more and more wind power generation integrated into power systems, the complexity of simulation will increase greatly if wind farms are modeled in detail. Thus, it is critical to develop dynamic equivalent methods for wind farms. The dynamic response characteristics of permanent magnet synchronous generator-wind turbine generators (PMSG-WTGs) are not only influenced by their control strategies, but also by the operating wind speeds and the fault severities. Thus, this paper proposes a dynamic equivalent method for a PMSG-WTG based wind farm considering the wind speeds and the fault severities. Firstly, we propose a clustering method based on the operating wind speed and the terminal voltage of each PMSG-WTG at the end of the fault. Then, a single-machine equivalent method is introduced for each cluster of PMSG-WTGs. For the cluster of PMSG-WTGs with active power ramp recovery process, an equivalent model with segmented ramp rate limitation for active current is designed. In order to obtain the clustering indicators, a simulation-based iterative method is put forward. Eventually, the efficiency and accuracy of the proposed method are verified by the simulation results.

Environmental Impact Assessment of Onshore Wind Power Plants: A Case Study of a 50 MW Wind Power Plant in Northeastern Thailand

This research aims to assess the environmental feasibility of a wind power plant by investigating its noise disturbances, shadow flicker, and zones of visual influence. The model is applied as a case study for a 50 MW wind power plant, located in the Nakhon Ratchasima province of northeastern Thailand. The acoustic noise emissions were analyzed using the sound propagation and absorption models under the wind conditions on the site studied. The shadow flicker around each wind turbine generator, in terms of the number of hours per year, was also simulated along with the analysis of the zones of visual influence according to the number of wind turbines that can be seen by an observer from a certain distance. The results show a maximum sound level of 47 dBA, within the allowed limits of the 50 dBA legislation of the Department of Pollution Control of the Royal Thai Government. Similarly, the shadow flicker within 1 km of the wind turbines is 10 hours/year, well below the international standard of 30 hours/year. Results of the zones of visual influence indicate that between 15 and 20 turbines are visible from observation points surrounding the potential wind power plant. The results applied to this case study suggest that the potential wind power plant is well-suited regarding its environmental impacts and should typically not incur negative impacts for the local communities. Studies like these are vital to gaining the trust of the communities living near wind power plants to address their concerns and minimize opposition.

Fluid–Structure Interaction Simulations of Wind Turbine Blades with Pointed Tips

The aerodynamic shapes of the blades are of great importance in wind turbine design to achieve better overall turbine performance. Fluid–structure interaction (FSI) analyses are normally carried out to take into consideration the effects due to the loads between the air flow and the turbine structures. A structural integrity check can then be performed, and the structural/material design can be optimized accordingly. In this study, three different tip shapes are investigated based on the original blade of the test wind turbine (Phase VI) from the National Renewable Energy Laboratory (NREL). A one-way coupled simulation of FSI is conducted, and results with a focus on stresses and deformations along the span of the blade are investigated. The results show that tip modifications of the blade have the potential to effectively increase the power generation of wind turbines while ensuring adequate structural strength. Furthermore, instead of using more complicated but computationally expensive techniques, this study demonstrates an effective approach to making quality observations of this highly nonlinear phenomenon for wind turbine blade design.

The Icing Characteristics of a 1.5 MW Wind Turbine Blade and Its Influence on the Blade Mechanical Properties

Ice accumulation significantly impacts the mechanical properties of wind turbine blades, affecting power output and reducing unit lifespan. This study explores the icing characteristics and their effects on a 1.5 megawatt (MW) wind turbine blade’s mechanical properties under various conditions, including wind speeds of 5 m per second (m/s) and 10 m per second, temperatures of −5 degrees centigrade (°C) and −10 degrees centigrade, and different liquid water contents, by using icing wind tunnel tests and structural statics analysis. The research reveals that ice predominantly forms in an irregular pattern on the leading edge of the blade. It is easy to produce corner ice and ice skating when the icing temperature and wind speed are higher, and the icing surface is rougher. When the other conditions remain unchanged, the decrease in temperature, an increase in wind speed, or a rise in liquid water content all lead to an increase in the average thickness of icing and the volume of icing at the leading edge, with the effect of the wind speed on the two being 147.8% and 147.9%, the effect of the liquid water content on the two being 39.9% and 53.5%, and the effect of the temperature on the two being 24.6% and 13.2%. The study finds that the blade tip experiences the maximum displacement in both iced and non-iced states, although the positions of peak equivalent stress and strain vary. The above study will also provide references for the design of new wind turbine blades and the anti-icing maintenance of wind turbine generator sets.

Wind turbine generator early fault diagnosis using LSTM-based stacked denoising autoencoder network and stacking algorithm

ABSTRACT To reduce the significant economic losses caused by the fault deterioration of wind turbine generators, it is urgent to detect and diagnose the early faults of generators. The existing condition monitoring and fault diagnosis (CMFD) methods have disadvantages of less considering data temporal characteristic, acquiring early faults with difficulty, and having lower diagnostic accuracy. To address those limitations, a novel LSDAE-stacking CMFD method of generators was proposed. Specifically, a multivariate spatiotemporal condition monitoring model (LSDAE) was established by combining the LSTM and SDAE networks, which can detect generator early anomalies through real-time monitoring the reconstruction residual. Then, based on the stacking ensemble algorithm, a multi-classification fault diagnosis model (Stacking) was constructed to identify early fault types, which can integrate advantages of different base-classifiers to achieve a better diagnostic accuracy. Case studies on three actual generator failures were employed to validate the effectiveness and accuracy of the proposed LSDAE-stacking method. The results illustrated that, compared with conventional SDAE model, the proposed LSDAE model had higher reconstruction precision and superior early-fault-warning capacities. And compared with traditional algorithms such as SVM, RF, AdaBoost, GBDT and XGBoost, the constructed Stacking model can effectively identify the fault types of generators and had higher diagnostic accuracy.

EXPERIMENTAL DEMONSTRATION OF ELECTRICAL POWER GENERATION USING STATIONARY EXERCISE BICYCLE COUPLED WITH WIND TURBINE REGULATOR

The small power generation using exercise bicycle is one of the current areas patronized by researchers. This is due to the two major benefits obtainable from the exercise machine, the benefit of exercising one’s body and the utilization of electrical power generated. Wind turbine regulator is specifically designed to regulate the output voltage of a wind turbine generator, which is characterized by varying speed and hence varying output power. The exercise bicycle driven alternator has a similarity with wind turbine generator in terms of variable speed, especially when ridden by different personalities. This paper demonstrates how small power can be generated using exercise bicycle. Further, the paper analyzes the performance of the by regulating its output using small wind turbine regulator. The result shows that, a regulated output within the range of 12V is obtained for all the tested loads, which makes the system more compatible with all types of 12V DC loads. Also the excitation voltage of the machine is improved from 4.5V (1.22A) using the diodes rectifier to 2.5V (0.81A) when the wind turbine regulator is used. With the improved power generation in this work the exercise bicycle will be a better alternative source for small power generation which can be used in DC lightings, DC fans, charging batteries and laboratory experiments.

Bearings faults and limits in wind turbine generators

The detection of sudden faults in wind turbine generator (WTG) is a complex task, especially in bearings. Usually, the evaluation of methodologies such as vibration, ultrasound, and bearing temperatures are widely used in predictive maintenance, an important aspect for the traditional approach, in wind turbine fault detection, is the limited analysis with a single variable as vibration, or temperature. For instance, these sensors detect 5–20% of torsional vibration in the drivetrain and 55% has a failure due to lubricant problem, 20% for solid contamination or 9% for the incorrect application of the bearing. Consequently, to solve this limitation and failures modes, this research evaluated the limits and focused on the early detection of bearing faults in wind generators; it utilized a multi-stage approach involving Random Forest, XGBoost, Light XGB, and Logistic Regression, followed by probability scores and optimal features with a search grid validation, in addition, validated results through finite element modeling, Boroscopy, and vibration analysis. Hence, the database considers faults for bearings, gearboxes, and for normal operation; with the vibration analysis regarding 8,711,808 samples used for validating process. The result of the study is the detection of sudden failures five days before vibration analysis with high classification accuracy of 99.994%, recall of 99.982%, F1 score of 98.124%, kappa 99.330%, and a test set time of 22.82 s. This new approach provides an early detection of sudden failures compared to traditional vibration analysis in bearings and gearboxes.