| Autor: |
Alireza Ghorbanpoor Lafmejani, S.M.H. Karimian, Mohammad Sadegh Moradi Ghareghani |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Cleaner Engineering and Technology, Vol 22, Iss , Pp 100801- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2666-7908 |
| DOI: |
10.1016/j.clet.2024.100801 |
| Popis: |
In the present work, a new configuration of the three-part blade (3-PB) Vertical Axis Wind Turbine (VAWT) is introduced. This new configuration is designed to further improve the aerodynamic performance of the 3-PB VAWT by tilting all three parts of every single blade along its central chord line. An optimization process is conducted to find the best tilt angle of blade parts in order to maximize the average total torque coefficient. The optimization process is applied to reference 3-PB VAWT with the help of a Genetic Algorithm (GA) and Artificial Neural Network (ANN) using the solutions of three-dimensional Reynolds averaged Navier-Stokes (RANS) equations at wind speed of 7 m/s and tip speed ratios from 0.44 to 1.77. Having analyzed different sets of tilt angles, a configuration with tilt angles of 30°, 31° , and 30° with respect to part 1, 2, and 3 was detected to be the best choice. The tilted 3-PB VAWT shows promising improvements in most tip speed ratios. Among them, a maximum improvement of 42.99% on the average of the total torque coefficient occurred at tip speed ratio of 0.89. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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