ESTIMATION OF CAPACITOR BANK SWITCHING OVERVOLTAGES USING ARTIFICIAL NEURAL NETWORK
journal of electrical engineering • 2017
معلومات البحث
المؤلفون
Sayed A. Ward;Mahmoud N. Ali;Hesham S. Ali
الكلمات المفتاحية
Capacitor bank energization, switching
overvoltages, power factor correction, artificial neural
network.
المجلة العلمية
journal of electrical engineering
الناشر
Hesham Said Abd Elmonsif Ali
المجلد
5/2015
العدد
2
الصفحات
172
publication.type
International
رابط البحث
Open Link
المواد المرفقة
Not Available
الملخص
According to power quality concerns, the
insertion of capacitor banks into the electrical power system
is interested in the case of power factor compensation and
voltage support. Due to capacitor bank switching process, a
transient overvoltage appears on the system and represents
hazard on equipment insulations. In this paper the capacitor
bank switching overvoltage dependent parameters are
studied and the artificial neural network (ANN) is used to
estimate this overvoltage. ANN is trained according to the
factors that affect the overvoltage. ANN training data is
provided by MATLAB/Simulink environment. The simulated
results show that the proposed technique can estimate the
peak values and durations of capacitor bank switching
overvoltages with good accuracy.
insertion of capacitor banks into the electrical power system
is interested in the case of power factor compensation and
voltage support. Due to capacitor bank switching process, a
transient overvoltage appears on the system and represents
hazard on equipment insulations. In this paper the capacitor
bank switching overvoltage dependent parameters are
studied and the artificial neural network (ANN) is used to
estimate this overvoltage. ANN is trained according to the
factors that affect the overvoltage. ANN training data is
provided by MATLAB/Simulink environment. The simulated
results show that the proposed technique can estimate the
peak values and durations of capacitor bank switching
overvoltages with good accuracy.
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