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Multi objective genetic algorithm controller's tuning for load frequency control in electric power systems / Mohamed Ahmed Mohamed Mahmoud Tammam ; Supervised A. A. Hamid Seif , M. A. E. Soliman M. A. Moustafa Hassan

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Mohamed Ahmed Mohamed Mahmoud Tammam , 2011Description: 153 P. : charts ; 30cmOther title:
  • استخدام النظام الجينى متعدد الاهداف لضبط المتحكم لتردد الحمل فى انظمة القوى الكهربية [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: In an interconnected power system as a power load demand varies randomly both area frequency and tie - line power also vary . Frequency is a major stability criterion in power system so active power balance and contant frequency are required . Thesis proposed two controllers applied to a single two - area power system by using the theory of multi objective genetic algorithms the performance of proposed intelligent controllers has been thoroughly compared and analyzed with the conventional ther artificial intelligent controllers
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Item type Current library Home library Call number Copy number Status Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.07.M.Sc.2011.Mo.M (Browse shelf(Opens below)) Not for loan 01010110056647000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.07.M.Sc.2011.Mo.M (Browse shelf(Opens below)) 56647.CD Not for loan 01020110056647000

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

In an interconnected power system as a power load demand varies randomly both area frequency and tie - line power also vary . Frequency is a major stability criterion in power system so active power balance and contant frequency are required . Thesis proposed two controllers applied to a single two - area power system by using the theory of multi objective genetic algorithms the performance of proposed intelligent controllers has been thoroughly compared and analyzed with the conventional ther artificial intelligent controllers

Issued also as CD

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