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العنوان
Recognition of Power Quality Events Using Artificial Neural Networks /
المؤلف
Abd Elmomen,Amany Hamdy
هيئة الاعداد
باحث / امانى حمدى عبد المؤمن
مشرف / محمد عبد اللطيف بدر
مشرف / المعتز يوسف عبد العزيز
مناقش / حسن محمد محمود مصطفى
مناقش / عادل يوسف حنا الله
تاريخ النشر
2013
عدد الصفحات
123p.:
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
الهندسة الكهربائية والالكترونية
تاريخ الإجازة
1/1/2013
مكان الإجازة
جامعة عين شمس - كلية الهندسة - قوى كهربية
الفهرس
Only 14 pages are availabe for public view

from 153

from 153

Abstract

Power quality is a term which includes all what is ideally required by a
customer to operate his equipment whatever industrial, agricultural or
even domestic, in high and proper order. In fact all modern electrical
utilities take power quality consideration very serious. Even some
penalties are applied to both sides; customers and utilities, who may
destroy or even disturb power quality. This thesis presents three stages
of a research work concerned with power quality issues in electric
power distribution networks. The first one the power quality research
works on the distribution system of the residential city. The Energy
Technology Assistance Program (ETAP) is used in modeling the
distribution system for symmetrical components and simulating the
processes of overvoltage and undervoltage caused by system faults
changes in loads and switching of capacitor banks. The simulation
results are analysed and compared with relevant standards for
evaluating the qualit y of power in the distribution system. The second
stage is used the Power Systems CAD Program (PSCAD) in modeling
the distribution system with unsymmetrical components and simulating
the process of voltage unbalance caused by system abnormal conditions
changes in loads. The third stage is the recognition of power qualit y
disturbances using neural networks. The simulation results work as
learning data to neural networks to detect and classify different power
quality signal types efficiently. Various steady state events are tested,
such as overvoltage and undervoltage and voltage unbalance.
Recognition of power quality events by analyzing the voltage
waveform disturbances is a very important task in the power system
monitoring.