Delegates are invited to meet and discuss with the poster presenters during the poster presentation sessions between 10:30-11:30 and 16:00-17:00 on Thursday, 19 November 2015.
Lead Session Chair:
Stephan Barth, ForWind - Center for Wind Energy Research, Germany
Khaled Yassin (1) F Aya Diab (1) Zakaria Ghoneim (1)
(1) Faculty of Engineering, Ain Shams University, Cairo, Egypt
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Presenter's biographyBiographies are supplied directly by presenters at EWEA 2015 and are published here unedited
Khaled Yassin is a mechanical engineer and M.Sc. student at Faculty of Engineering, Ain Shams University and he had his B.Sc. from the same university. For five years, he has been working in the field of engineering consulting. His research is focused on design and optimization of wind turbine blades.
PosterDownload poster (5.55 MB)
Design Optimization of a Site-Specific Wind Turbine Blades Using a Genetic Algorithm: Structural Considerations
In the last few decades, a lot of attention has been focused on renewable energy and its associated technologies driven primarily by the instability in the energy market as well as the catastrophic consequences of climate change due to global warming. Because wind energy is the fastest growing forms of renewable energy, the wind industry is currently targeting the optimized site-specific wind turbine designs in order to minimize the cost of energy (COE) produced. This work aims to optimize the structural design of a 5 MW wind turbine rotor subject to the harsh saharan environmental conditions of the Middle East and North Africa (MENA) region that is known for its high temperature and dust loaded air.
The reduction of the produced COE is done by design and optimization of a 5MW wind turbine rotor according to the wind conditions of Zaafarana site located on the coast of Gulf of Suez, Egypt. This site has an average wind speeds that reaches 11 m/s, high humidity, high temperature,and dusty wind in most times of the year.
Main body of abstract
The aerodynamic profile of the rotor is designed using airfoils with low sensitivity to surface contamination and optimized using a Genetic Algorithm (GA) to maximize the annual energy production while simultaneously reduce its weight through a cost function; hence reducing the COE. The developed turbine rotor design is tested for structural integrity commensurate with IEC standards.
This research resulted in a new design that is designed according the specified site conditions of wind speeds and dust loaded air and has a reduced COE produced by this wind turbine.
The learning objectives of this research are the importance of designing the wind turbine rotor for a specific site with a specific wind speeds distribution over the year and the importance of including the factor of dust accumulation on the rotor in the design process.