Artificial neural network application for prediction of reactive power compensation under line outage contingency

Author

Rai, Atul ; Babu, D. Suresh ; Venkataramu, P.S. ; Nagaraja, M.S.

Author_Institution

Electr. & Electron. Eng., GGITM, Bhopal, India

fYear

2013

fDate

6-8 Feb. 2013

Firstpage

355

Lastpage

359

Abstract

Static VAR Compensator is a variable impedance device where the current through a reactor is controlled using back to back thyristor connected valves. In this paper a successful attempt has been made to design an ANN architecture which predicts the quantum of compensation to be provided to the system for a specific line outage contingency in order to improve the system performance. The study is carried out on an IEEE-30 bus system using MATLAB software.

Keywords

neural nets; power engineering computing; reactive power; reactors (electric); static VAr compensators; thyristor applications; ANN architecture; IEEE-30 bus system; Matlab software; artificial neural network application; back-to-back thyristor connected valves; line outage contingency; reactive power compensation prediction; reactor; static VAR compensator; variable impedance device; Artificial neural networks; Educational institutions; Power system stability; Reactive power; Static VAr compensators; Training; Voltage control; ADALINE; ANN; Line outage contingency; Reactive power compensation; SVC;

fLanguage

English

Publisher

ieee

Conference_Titel

Power, Energy and Control (ICPEC), 2013 International Conference on

Conference_Location

Sri Rangalatchum Dindigul

Print_ISBN

978-1-4673-6027-2

Type

conf

DOI

10.1109/ICPEC.2013.6527681

Filename

6527681