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Auteur principal: Sandra Milena Pérez Londoño
Format: Artículo científico
Langue:en
Publié: Universidad de Antioquia 2008
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Accès en ligne:https://www.redalyc.org/articulo.oa?id=43004511
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author Sandra Milena Pérez Londoño
author_facet Sandra Milena Pérez Londoño
contents Oscillation Control in a Synchronous Machine using a Neural based PSS Sandra Milena Pérez Londoño Juan José Mora Flórez Alfonso Alzate Ingeniería neural nets synchronous machine Power system stabilizer This paper presents the methodological design and the laboratory test of neural net based power system stabilizer (PSS). The architecture of the proposed PSS uses two neural networks, one neural based controller which is used to generate a supplementary control signal to the excitation system, and an additional neural net used to improve the performance of the neural based controller. In order to guarantee the correct operation of the proposed PSS, it is trained by using data obtained from several machine operating conditions and a variety of disturbances. The effectiveness is demonstrated by testing the proposed approach in a real synchronous machine in a laboratory facility. 2008 artículo científico 0120-6230 https://www.redalyc.org/articulo.oa?id=43004511 en http://www.redalyc.org/revista.oa?id=430 Revista Facultad de Ingeniería Universidad de Antioquia application/pdf Universidad de Antioquia Revista Facultad de Ingeniería Universidad de Antioquia (Colombia) Num.45
format Artículo científico
id redalyc_43004511
language en
publishDate 2008
publisher Universidad de Antioquia
spellingShingle Oscillation Control in a Synchronous Machine using a Neural based PSS
Sandra Milena Pérez Londoño
Ingeniería
neural nets
synchronous machine
Power system stabilizer
Oscillation Control in a Synchronous Machine using a Neural based PSS Sandra Milena Pérez Londoño Juan José Mora Flórez Alfonso Alzate Ingeniería neural nets synchronous machine Power system stabilizer This paper presents the methodological design and the laboratory test of neural net based power system stabilizer (PSS). The architecture of the proposed PSS uses two neural networks, one neural based controller which is used to generate a supplementary control signal to the excitation system, and an additional neural net used to improve the performance of the neural based controller. In order to guarantee the correct operation of the proposed PSS, it is trained by using data obtained from several machine operating conditions and a variety of disturbances. The effectiveness is demonstrated by testing the proposed approach in a real synchronous machine in a laboratory facility. 2008 artículo científico 0120-6230 https://www.redalyc.org/articulo.oa?id=43004511 en http://www.redalyc.org/revista.oa?id=430 Revista Facultad de Ingeniería Universidad de Antioquia application/pdf Universidad de Antioquia Revista Facultad de Ingeniería Universidad de Antioquia (Colombia) Num.45
title Oscillation Control in a Synchronous Machine using a Neural based PSS
topic Ingeniería
neural nets
synchronous machine
Power system stabilizer
url https://www.redalyc.org/articulo.oa?id=43004511