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Maximization of wind energy conversion system using artificial intelligent techniques / Omar Hamdi Hussein Mohamed ; Supervised Ahmed Mohamed Ahmed Ibrahim , Mahmoud Mohamed Sayed , Tarek Abdelbadea Boghdady

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Omar Hamdi Hussein Mohamed , 2018Description: 106 P. ; 30cmOther title:
  • تعظيم نظام تحويل طاقة الرياح باستخدام أساليب ذكاء اصطناعية [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electrical Power and Machines Summary: Wind has been utilized as a source of power in different applications throughout the years. Recently, due to the depletion of fossil fuel, environmental impact, and the gross in energy demand all over the world, as a result, the desire to find an alternative renewable energy sources is increased. A literature review is introduced about wind energy production and new installed capacity in Egypt and worldwide. Many optimization methods like GA, BBO, LBBO, and CSA have been applied to tune the PI parameters to obtain the optimum performance for the wind farm. In addition, an adaptive PI Neural Network (PINN) controller is introduced to tune PI parameters online and comparing its performance with the conventional PI controller with different operating conditions. The system is tested under different operating condition such as wind speed variation and faults
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.07.M.Sc.2018.Om.M (Browse shelf(Opens below)) Not for loan 01010110077267000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.07.M.Sc.2018.Om.M (Browse shelf(Opens below)) 77267.CD Not for loan 01020110077267000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electrical Power and Machines

Wind has been utilized as a source of power in different applications throughout the years. Recently, due to the depletion of fossil fuel, environmental impact, and the gross in energy demand all over the world, as a result, the desire to find an alternative renewable energy sources is increased. A literature review is introduced about wind energy production and new installed capacity in Egypt and worldwide. Many optimization methods like GA, BBO, LBBO, and CSA have been applied to tune the PI parameters to obtain the optimum performance for the wind farm. In addition, an adaptive PI Neural Network (PINN) controller is introduced to tune PI parameters online and comparing its performance with the conventional PI controller with different operating conditions. The system is tested under different operating condition such as wind speed variation and faults

Issued also as CD

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