Bulletin of the American Physical Society
71st Annual Meeting of the APS Division of Fluid Dynamics
Volume 63, Number 13
Sunday–Tuesday, November 18–20, 2018; Atlanta, Georgia
Session D06: Energy Harvesting and Power Generation II
2:30 PM–4:40 PM,
Sunday, November 18, 2018
Georgia World Congress Center
Room: B208
Chair: Kiran Bhaganagar, University of Texas at San Antonio
Abstract ID: BAPS.2018.DFD.D06.2
Abstract: D06.00002 : Optimization Of Vertical Axis Wind Turbines Using Design-By-Morphing
2:43 PM–2:56 PM
Presenter:
Haris Moazam Sheikh
(Univ of California - Berkeley)
Authors:
Haris Moazam Sheikh
(Univ of California - Berkeley)
Philip S Marcus
(Univ of California - Berkeley)
Currently, Horizontal Axis Wind Turbines (HAWTs) driven by aerodynamic lift are the most common form of commercial wind turbines. However, many studies have shown that Vertical Axis Wind Turbines (VAWTs) may be more efficient because VAWTs can be packed more closely into arrays than HAWTs without losing efficiency and are in fact more efficient as compared to a standalone VAWT. Thus, per unit area of land (or sea), more energy can be produced with VAWTs than HAWTs, making them more economically viable. The present study focuses on optimization of a standalone VAWT and its supplementary structures as well as position optimization of VAWT triplets to optimize their power output. The study utilizes novel ‘Design-by-Morphing’ technique, using four hybrid lift and drag based blades as baseline shapes and morphing them to produce novel blade shapes by assigning weights to these baseline shapes. These shapes were then analyzed using Computational Fluid Dynamics (CFD) and machine learning was used to optimize a multi-objective performance function. These optimized turbine and supplementary structure were then used to analyze an optimum arrangement of VAWT triplets to increase array efficiency.
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.DFD.D06.2
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