Hydrodynamic optimization of high-performance blade sections for stall regulated hydrokinetic turbines using Differential Evolution Algorithm
Ocean Engineering, ISSN: 0029-8018, Vol: 220, Page: 108389
2021
- 16Citations
- 45Captures
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Article Description
Hydrokinetic turbines are electromechanical devices, which convert the kinetic energy of freely flowing water into electricity without accumulating water. Turbine blades are generated by optimally combining one or more types of blade sections. The performance of blade sections is quite important directly affecting the power coefficient of the rotor. Since hydrokinetic technology is relatively a new branch of renewable energy, blade sections optimized for wind turbines or aviation applications had hitherto been used. However, hydrodynamics of water should be better considered during design processes. The main scope of this study is to optimize blade sections specifically for stall regulated hydrokinetic turbines considering high hydrodynamic forces, cavitation, leading-edge contamination, and ideal stall behavior. Differential Evolution Algorithm (DEA) was employed for the optimization process. Five different primary hydrofoil families were optimized and they have been scaled for various regions along the blade. Lift, drag, transition, and pressure coefficient performances of optimized sections have been analyzed and discussed with mostly used NACA, RISØ, and NREL sections. The optimized hydrofoils are found to deliver quite successful performance for hydrokinetic turbines based on design objectives, constraints, and comparing to the most preferred sections.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0029801820312968; http://dx.doi.org/10.1016/j.oceaneng.2020.108389; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85097464715&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0029801820312968; https://api.elsevier.com/content/article/PII:S0029801820312968?httpAccept=text/xml; https://api.elsevier.com/content/article/PII:S0029801820312968?httpAccept=text/plain; https://dul.usage.elsevier.com/doi/; https://dx.doi.org/10.1016/j.oceaneng.2020.108389
Elsevier BV
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