The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON CIRCUITS AND SYSTEMS
Transactions ID Number: 53-391
Full Name: Saeid Veysi Raygani
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Age: ON
Sex: Male
Address: Iran University of Science and Technology, Hengam street, Narmak, Tehran
Country: IRAN
Tel: +989124077065
Tel prefix: +982122530680
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E-mail address: said_visi@yahoo.com
Other E-mails: said.visi.62@gmail.com
Title of the Paper: svc implementation using neural networks for an ac electrical railway
Authors as they appear in the Paper: Saeid Veysi Raygani, Moaveni Bijan, Fazel Seyed Saeed, Tahavorgar Amir
Email addresses of all the authors: said_visi@yahoo.com, b_moaveni@iust.ac.ir, fazel@iust.ac.ir, a_tahavorgar@rail.iust.ac.ir
Number of paper pages: 11
Abstract: This paper presents an on-line method for implementation of a static var compensator (SVC) in a real ac autotransformer (AT)-fed electrical railway for reactive power compensation using Neural Networks (NN). Genetic algorithm (GA) can be the off-line minimizing function for reactive power compensation. Consequently, the nonlinear auto-regressive model with exogenous Inputs networks in series-parallel arrangement (NARXSP) is implemented as a predictor and methodology in order to diminish calculation time and making this method practicable. To study load flow and reactive power compensation for this unique system, forward/backward sweep (FBS) load flow method is applied. MATLAB software is used for programming and simulations.
Keywords: Neural Network , Reactive Power Compensation, Static Var Vompensator , Genetic Algorithm , AC Electrical Railways Load Flow, Forward/Backward Sweep
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How Did you learn about congress: neural networks and reactive power compensation
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