Getting more from the wind: Recent advancements and challenges in generators development for wind turbines

Chang, Clifford Choe Wei; Ding, Tan Jian; Ping, Tan Jian; Chao, Kang Chia; Bhuiyan, Mohammad Arif Sobhan

doi:10.1016/j.seta.2022.102731

Cited by 13 publications

(6 citation statements)

References 49 publications

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“…Wind turbines have become one of the major developments in the global renewable energy sector [ 1 ].They are widely applied across various countries and regions as a significant component of the power supply [ 2 , 3 ]. Wind turbines are subjected to unstable working conditions, as well as exposed to high wind speeds, extreme temperatures, humidity, and corrosive climates for long periods of time [ 4 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of Wind Turbine Gearbox Based on Modified Hierarchical Fluctuation Dispersion Entropy of Tan-Sigmoid Mapping

Wang,

2024

Entropy

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Vibration monitoring and analysis are important methods in wind turbine gearbox fault diagnosis, and determining how to extract fault characteristics from the vibration signal is of primary importance. This paper presents a fault diagnosis approach based on modified hierarchical fluctuation dispersion entropy of tan-sigmoid mapping (MHFDE_TANSIG) and northern goshawk optimization–support vector machine (NGO–SVM) for wind turbine gearboxes. The tan-sigmoid (TANSIG) mapping function replaces the normal cumulative distribution function (NCDF) of the hierarchical fluctuation dispersion entropy (HFDE) method. Additionally, the hierarchical decomposition of the HFDE method is improved, resulting in the proposed MHFDE_TANSIG method. The vibration signals of wind turbine gearboxes are analyzed using the MHFDE_TANSIG method to extract fault features. The constructed fault feature set is used to intelligently recognize and classify the fault type of the gearboxes with the NGO–SVM classifier. The fault diagnosis methods based on MHFDE_TANSIG and NGO–SVM are applied to the experimental data analysis of gearboxes with different operating conditions. The results show that the fault diagnosis model proposed in this paper has the best performance with an average accuracy rate of 97.25%.

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Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of Wind Turbine Gearbox Based on Modified Hierarchical Fluctuation Dispersion Entropy of Tan-Sigmoid Mapping

Wang,

2024

Entropy

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“…In this space, the domain of wind energy research, a foremost objective is to reduce the Levelized Cost of Energy (LCoE) [2][3][4], with many advancements in the field making wind energy more available, more productive, and cheaper. This can include many technologies or features which improve operation of the turbine, ranging from fatigue monitoring and reduction, structural improvements, aerodynamic improvements and modeling efforts, and materials technologies, and can impact onshore [5] and offshore [6] turbines [7,8].…”

Section: Introductionmentioning

confidence: 99%

Review of Data-Driven Models in Wind Energy: Demonstration of Blade Twist Optimization Based on Aerodynamic Loads

Roetzer,

Li,

Hall

2024

Preprint

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With the increasing use of data-driven modeling methods new approaches to complex problems in the field of wind energy can be addressed. Topics reviewed through literature include wake modeling, performance monitoring and controls applications, condition monitoring and fault detection, and other data-driven research. Literature shows the advantages of data-driven methods reduce computational expense or complexity, particularly in the cases of wake modeling and controls, as well as various data-driven methodologies’ aptitude for predictive modeling and classification, as in the cases of fault detection and diagnosis. Significant work exists for fault detection while less work is found for controls applications. A methodology for creating data-driven wind turbine models for arbitrary performance parameters is proposed. Results are presented utilizing the methodology to create wind turbine models relating active adaptive twist to steady-state rotor thrust as a performance parameter of interest. Resulting models are evaluated by comparing root-mean-square-error (RMSE) on both the training and validation data sets, with Gaussian Process Regression (GPR), deemed an accurate model for this application. The resulting model undergoes particle swarm optimization to determine the optimal aerostructure twist shape at a given wind speed with respect to the modeled performance parameter, aerodynamic thrust load. The optimization process shows an improvement of 3.15% in thrust loading for the 10 MW reference turbine, and 2.66% for the 15 MW reference turbine.

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“…Large-scale wind turbines encountered significant challenges. One of these challenges is changing the wind direction over a short period (Chang et al, 2022). This challenge is particularly pronounced in southern Jordan, where many wind turbine farms have been established.…”

Section: Introductionmentioning

confidence: 99%

An investigation of a 3D printed micro-wind turbine for residential power production

Shalby

Salah

Matarneh

et al. 2023

Int. J. Renew. Energy Dev.

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The wind energy sector is rapidly growing and has become one of the most important sources of renewable power production. New technologies are being developed to increase energy production. This study focuses on developing and evaluating a 3-D printed micro-wind turbine system for residential electricity production. The effectiveness of using Poly Lactic Acid material for model production was assessed using the SolidWorks environment. Then, three–dimensional CFD model was developed to simulate a micro-wind turbine. The CFD model was validated in good agreement against scale physical model experiments performed in a wind tunnel. The results demonstrated that the 5-blade micro-wind turbine design was the most effective under the tested conditions, with a low cut-in speed and the ability to operate under torque up to 70 N.m. Finally, the currently available manufacturing processes for micro-wind turbines have been evaluated. Future work should evaluate the performance of the MWT system under realistic conditions in a site test to determine energy production and total efficiency

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Getting more from the wind: Recent advancements and challenges in generators development for wind turbines

Cited by 13 publications

References 49 publications

Fault Diagnosis of Wind Turbine Gearbox Based on Modified Hierarchical Fluctuation Dispersion Entropy of Tan-Sigmoid Mapping

Fault Diagnosis of Wind Turbine Gearbox Based on Modified Hierarchical Fluctuation Dispersion Entropy of Tan-Sigmoid Mapping

Review of Data-Driven Models in Wind Energy: Demonstration of Blade Twist Optimization Based on Aerodynamic Loads

An investigation of a 3D printed micro-wind turbine for residential power production

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