An Integrated Control and Design Framework for Optimizing Energy Capture and Component Life for a Wind Turbine Variable Ratio Gearbox

2015 ◽  
Vol 137 (2) ◽  
Author(s):  
John F. Hall ◽  
Dushyant Palejiya ◽  
Mohamed L. Shaltout ◽  
Dongmei Chen
Keyword(s):  
Wind Turbine ◽  
High Efficiency ◽  
Integrated Control ◽  
Critical Role ◽  
Maximum Energy ◽  
Variable Ratio ◽  
Wind Turbine Gearbox ◽  
Energy Capture ◽  
Development Framework ◽  
System Life

Small wind turbines are a promising technology that can provide renewable power to rural and remote communities. In order to increase the efficiency and competitiveness of small wind technology, it is necessary to maximize the wind energy capture and to prolong the turbine system life. Accordingly, this paper presents an integrated development framework that optimizes component design goals, including durability and minimal gearbox mass, with the control objective of producing maximum energy over the turbine system’s 20-yr life. This study focuses on the wind turbine gearbox, which plays a critical role in achieving high efficiency and extended system life. A variable ratio gearbox (VRG) previously developed by the authors is used as an example to demonstrate the methodology. In this paper, an algorithm developed for optimizing the VRG gear ratio is integrated with the design selection of commercially available gears, which will be used to construct the VRG gearbox. The proposed multi-objective framework is capable of identifying the optimal gearsets based on a trade-off between selecting gearsets that maximize wind turbine efficiency and choosing gearsets that best meet the design requirements.

Optimal Control of a Wind Turbine With a Variable Ratio Gearbox for Maximum Energy Capture and Prolonged Gear Life

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Mohamed L. Shaltout ◽  
John F. Hall ◽  
Dongmei Chen
Keyword(s):  
Optimal Control ◽  
Wind Energy ◽  
Wind Turbine ◽  
Gear Tooth ◽  
Tangential Force ◽  
Maximum Energy ◽  
Variable Ratio ◽  
New Approach ◽  
Control Approach ◽  
Energy Capture

An optimal control approach for a wind turbine drivetrain with a variable ratio gearbox is presented. The objective is to find the optimum shifting sequence of the variable ratio gearbox in order to maximize power generation and extend gear life. The employment of a variable ratio gearbox enhances the capabilities of the wind turbine to cope with wind speed variations. Based on the authors' preliminary study, the gear ratios of the variable ratio gearbox were carefully selected to maximize the wind energy capture. In this paper, a new control approach is proposed to achieve both extended gear service life and optimal energy harvesting. This new approach finds the gear shifting sequence that will minimize the tangential force on the gear tooth while maximizing the wind energy capture. The wind turbine drivetrain with a variable ratio gearbox is modeled and simulation results based on recorded wind data of different wind classes are presented and compared.

scholarly journals Moving Accelerometers to the Tip: Monitoring of Wind Turbine Blade Bending Using 3D Accelerometers and Model-Based Bending Shapes

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5337
Author(s):  
Theresa Loss ◽  
Alexander Bergmann
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Rotation Frequency ◽  
Real Data ◽  
Maximum Energy ◽  
Wind Turbine Blades ◽  
Energy Capture ◽  
Model Based ◽  
Blade Tip ◽  
Wind Profiles

Increasing the length of wind turbine blades for maximum energy capture leads to larger loads and forces acting on the blades. In particular, alternate bending due to gravity or nonuniform wind profiles leads to increased loads and imminent fatigue. Therefore, blade monitoring in operation is needed to optimise turbine settings and, consequently, to reduce alternate bending. In our approach, an acceleration model was used to analyse periodically occurring deviations from uniform bending. By using hierarchical clustering, significant bending patterns could be extracted and patterns were analysed with regard to reference data. In a simulation of alternate bending effects, various effects were successfully represented by different bending patterns. A real data experiment with accelerometers mounted at the blade tip of turbine blades demonstrated a clear relation between the rotation frequency and the resulting bending patterns. Additionally, the markedness of bending shapes could be used to assess the amount of alternate bending of the blade in both simulations and experiment.s The results demonstrate that model-based bending shapes provide a strong indication for alternate bending and, consequently, can be used to optimise turbine settings.

Methods for Increasing Region 2 Power Capture on a Variable-Speed Wind Turbine

2004 ◽  
Vol 126 (4) ◽  
pp. 1092-1100 ◽  
Author(s):  
Kathryn E. Johnson ◽  
Lee J. Fingersh ◽  
Mark J. Balas ◽  
Lucy Y. Pao
Keyword(s):  
Wind Turbine ◽  
Maximum Energy ◽  
Control Methods ◽  
Variable Speed ◽  
Rotor Speed ◽  
Energy Capture ◽  
Control Scheme ◽  
Variable Speed Wind Turbine ◽  
Power Capture ◽  
Speed Fluctuations

The standard region 2 control scheme for a variable-speed wind turbine, τc=Kω2, has several shortcomings that can result in significant power loss. The first of these is that there is no accurate way to determine the gain K; modeling programs are not accurate enough to represent all of the complex aerodynamics, and these aerodynamics change over time. Furthermore, it is not certain whether the value of K used in the standard control even provides for the maximum energy capture under real-world turbulent conditions. We introduce new control methods to address these issues. First, we show in simulation that using smaller values of K than the standard can result in increased energy capture. Second, we give simulation results showing that an optimally tracking rotor control scheme can improve upon the standard scheme by assisting the rotor speed in tracking wind-speed fluctuations more rapidly. Finally, we propose an adaptive control scheme that allows for maximum power capture despite parameter uncertainty.

Fault Diagnosis of Wind Turbine Gearbox Based on Improved QPSO Algorithm

2019 ◽  
Vol 12 (3) ◽  
pp. 277-283
Author(s):  
Jiatang Cheng ◽  
Yan Xiong
Keyword(s):  
Particle Swarm Optimization ◽  
Fault Diagnosis ◽  
Wind Turbine ◽  
Bp Neural Network ◽  
Quantum Particle ◽  
Particle Swarm ◽  
Wind Turbine Gearbox ◽  
Bp Network ◽  
Swarm Optimization ◽  
Quantum Particle Swarm Optimization

Background: The effective diagnosis of wind turbine gearbox fault is an important means to ensure the normal and stable operation and avoid unexpected accidents. Methods: To accurately identify the fault modes of the wind turbine gearbox, an intelligent diagnosis technology based on BP neural network trained by the Improved Quantum Particle Swarm Optimization Algorithm (IQPSOBP) is proposed. In IQPSO approach, the random adjustment scheme of contractionexpansion coefficient and the restarting strategy are employed, and the performance evaluation is executed on a set of benchmark test functions. Subsequently, the fault diagnosis model of the wind turbine gearbox is built by using IQPSO algorithm and BP neural network. Results: According to the evaluation results, IQPSO is superior to PSO and QPSO algorithms. Also, compared with BP network, BP network trained by Particle Swarm Optimization (PSOBP) and BP network trained by Quantum Particle Swarm Optimization (QPSOBP), IQPSOBP has the highest diagnostic accuracy. Conclusion: The presented method provides a new reference for the fault diagnosis of wind turbine gearbox.

The critical role of the coordination sphere in the high-efficiency blue-light emission from aminopyrazine metal-organic polymers

2021 ◽  
Vol 186 ◽  
pp. 109025
Author(s):  
João Humberto Dias Campos ◽  
Meiry Edivirges Alvarenga ◽  
Maykon Alves Lemes ◽  
José Antônio do Nascimento Neto ◽  
Freddy Fernandes Guimarães ◽  
...  
Keyword(s):  
Blue Light ◽  
Coordination Sphere ◽  
High Efficiency ◽  
Light Emission ◽  
Critical Role ◽  
Organic Polymers ◽  
Blue Light Emission ◽  
Metal Organic

scholarly journals Development of a wind turbine gearbox virtual load sensor using multibody simulation and artificial neural networks

2021 ◽  
Author(s):  
Baher Azzam ◽  
Ralf Schelenz ◽  
Björn Roscher ◽  
Abdul Baseer ◽  
Georg Jacobs
Keyword(s):  
Time Series ◽  
Wind Turbine ◽  
High Speed ◽  
Time Series Data ◽  
Development Trend ◽  
Series Data ◽  
Ann Model ◽  
Wind Turbine Gearbox ◽  
Virtual Sensor ◽  
Artificial Neural

AbstractA current development trend in wind energy is characterized by the installation of wind turbines (WT) with increasing rated power output. Higher towers and larger rotor diameters increase rated power leading to an intensification of the load situation on the drive train and the main gearbox. However, current main gearbox condition monitoring systems (CMS) do not record the 6‑degree of freedom (6-DOF) input loads to the transmission as it is too expensive. Therefore, this investigation aims to present an approach to develop and validate a low-cost virtual sensor for measuring the input loads of a WT main gearbox. A prototype of the virtual sensor system was developed in a virtual environment using a multi-body simulation (MBS) model of a WT drivetrain and artificial neural network (ANN) models. Simulated wind fields according to IEC 61400‑1 covering a variety of wind speeds were generated and applied to a MBS model of a Vestas V52 wind turbine. The turbine contains a high-speed drivetrain with 4‑points bearing suspension, a common drivetrain configuration. The simulation was used to generate time-series data of the target and input parameters for the virtual sensor algorithm, an ANN model. After the ANN was trained using the time-series data collected from the MBS, the developed virtual sensor algorithm was tested by comparing the estimated 6‑DOF transmission input loads from the ANN to the simulated 6‑DOF transmission input loads from the MBS. The results show high potential for virtual sensing 6‑DOF wind turbine transmission input loads using the presented method.

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