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العنوان
Application of Optimization Techniques to Electrical Power Distribution Networks \
المؤلف
Abd-Allah, Ramy Fakhry Gehead Hussein.
هيئة الاعداد
باحث / رامى فخرى جهيد عبد الله
مشرف / إمتثال نجم عبد الله صالح
emtethal_1934@yahoo.com
مشرف / ياسمين أبو السعود صالح متولى
مناقش / نبيل حسن محمود عباسى
abbasyna@hotmail.com
مناقش / محمود محمود عبد السلام
الموضوع
Mathematical Engineering.
تاريخ النشر
2017.
عدد الصفحات
111 p. :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
الهندسة (متفرقات)
تاريخ الإجازة
1/10/2017
مكان الإجازة
جامعة الاسكندريه - كلية الهندسة - هندسة الرياضيات و الفيزياء
الفهرس
Only 14 pages are availabe for public view

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Abstract

Power Losses in electrical distribution networks represents a great portion of the total amount of power lost from generation to distribution. Moreover, the overwhelming increase of the demand on electrical energy makes power loss reduction, in electrical power distribution networks, a vital and crucial research topic. This thesis reports on research conducted on radial electrical power distribution networks with a main target of reducing the system’s power loss, while satisfying the operational constraints of the electrical system. At First, an efficient Load flow algorithm specifically tailored for Radial Distribution Networks was developed and compared to other existing algorithms in terms of precision and Computational efficiency. The load flow problem was modeled and solved using Quadratically-Constrained Convex Program. Second, the Network Reconfiguration Problem was mathematically modeled and solved using Mixed Integer Quadratically-Constrained Convex Optimization Program. This program seeks the optimum on/off positions of line section switches and Tie-lines so that the distribution network is radial and operates at minimum loss subject to several operating constraints regarding the operation of the electrical power distribution networks. Both Problems Were Solved using CPLEX IBM ILOG Optimization Software. The newly adopted algorithm was compared to previous existing in terms of the objective function value and computational efficiency.