scholarly journals The optimal profile of wind generator blade modelling with CFD-method

2020 ◽  
Vol 1679 ◽  
pp. 052078
Author(s):  
Vadim Khudoyarov ◽  
Dmitry Samsonenko ◽  
Artyom Nikulin ◽  
Nikolai Barbashov ◽  
Leila Abdullina
2019 ◽  
Vol 2 (1) ◽  
pp. 8-16 ◽  
Author(s):  
P. A. Khlyupin ◽  
G. N. Ispulaeva

Introduction: The co-authors provide an overview of the main types of wind turbines and power generators installed into wind energy devices, as well as advanced technological solutions. The co-authors have identified the principal strengths and weaknesses of existing wind power generators, if applied as alternative energy sources. The co-authors have proven the need to develop an algorithm for the selection of a wind generator-based autonomous power supply system in the course of designing windmill farms in Russia. Methods: The co-authors have analyzed several types of wind turbines and power generators. Results and discussions: The algorithm for the selection of a wind generator-based autonomous power supply system is presented as a first approximation. Conclusion: The emerging algorithm enables designers to develop an effective wind generator-based autonomous power supply system.


Author(s):  
K.S. Klen ◽  
◽  
M.K. Yaremenko ◽  
V.Ya. Zhuykov ◽  
◽  
...  

The article analyzes the influence of wind speed prediction error on the size of the controlled operation zone of the storage. The equation for calculating the power at the output of the wind generator according to the known values of wind speed is given. It is shown that when the wind speed prediction error reaches a value of 20%, the controlled operation zone of the storage disappears. The necessity of comparing prediction methods with different data discreteness to ensure the minimum possible prediction error and determining the influence of data discreteness on the error is substantiated. The equations of the "predictor-corrector" scheme for the Adams, Heming, and Milne methods are given. Newton's second interpolation formula for interpolation/extrapolation is given at the end of the data table. The average relative error of MARE was used to assess the accuracy of the prediction. It is shown that the prediction error is smaller when using data with less discreteness. It is shown that when using the Adams method with a prediction horizon of up to 30 min, within ± 34% of the average energy value, the drive can be controlled or discharged in a controlled manner. References 13, figures 2, tables 3.


Author(s):  
Ivan Kabardin ◽  
Igor Naumov ◽  
R Mikelson ◽  
K Velte
Keyword(s):  

2005 ◽  
Vol 1 (03) ◽  
pp. 453-457
Author(s):  
S. Martín ◽  
◽  
M.P. Comech ◽  
S. Borroy ◽  
M. García-Gracia

2020 ◽  
Vol 4 (4) ◽  
pp. 56-63
Author(s):  
Victor N. ANTIPOV ◽  
◽  
Andrey D. GROZOV ◽  
Anna V. IVANOVA ◽  
◽  
...  

Author(s):  
Stefany Kariny dos Santos de Souza Queiroz ◽  
Pedro Celestino Neto ◽  
Isac Barbosa de Almeida ◽  
Clayton Antonio de Oliveira ◽  
Idalmir de Souza Queiroz Júnior

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