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العنوان
Switched Capacitor Active Power Filter Optimization Using Nature-Inspired Metaheuristic Algorithms \
المؤلف
Diab, Mai Ismail Mohamed Rashad.
هيئة الاعداد
باحث / مى اسماعيل محمد رشاد دياب
mai.diab@alex-eng.edu.eg
مشرف / تامر حلمى عبدالحميد
مشرف / سمير دغيدى عرفان
degedie@gmail.com
مشرف / محمد محمد صدقى الحبروك
eepgmmel@yahoo.com
مناقش / عمرو محمد عثمان الزواوى
amr.elzuwau@yahoo.com
مناقش / احمد انس الوجود هلال
الموضوع
Electrical Engineering.
تاريخ النشر
2019.
عدد الصفحات
75 p. :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
الهندسة الكهربائية والالكترونية
تاريخ الإجازة
27/2/2019
مكان الإجازة
جامعة الاسكندريه - كلية الهندسة - الهندسة الكهربائية
الفهرس
Only 14 pages are availabe for public view

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from 106

Abstract

The rapid increase of nonlinear loads connected to the power systems has resulted in numerous power quality problems. One of the main problems is the generated current harmonics, which distort the sinusoidal current waveform. Over the years, these harmonics have been mitigated using passive power filters, active power filter, and hybrid filters. The use of passive filters encounters the problems of being affected by the source impedance and the risk of resonance whereas active filters do not have those issues. Many active filters configurations have been utilized including the switched capacitor filters, which are less bulky, less expensive and use lower switching frequency than other types of active filters.This thesis offers a survey of the active filters configurations and categorizes the employment of switched capacitor circuits in the power system. One of the applications of the switched capacitor circuits is alleviating the current harmonics, which is the topic of this thesis. The proposed switched capacitor filter circuit is optimized using Nature-inspired Metaheuristic Algorithms, Ant Colony Optimization, and Genetic Algorithm, to obtain the optimum performance and minimize the total harmonic distortion of the source current.The proposed switched capacitor filter managed to alleviate the total harmonic distortion percentage in both nonlinear inductive load case and nonlinear capacitive load case using Ant Colony Optimization and Genetic Algorithm. Also, a collaboration between both Ant Colony Optimization and Genetic Algorithm is achieved in the case of the nonlinear capacitive load which enhanced the minimization results in this case.