Use of ANFIS Control Approach for SSSC based Damping Controllers Applied in a Two-area Power System

In an interconnected power system, low frequency electromechanical oscillations are initiated by normal small changes in system loads, and they become much worse following a large disturbance. Flexible AC Transmission System (FACTS) devices are widely recognized as powerful controllers for damping power system oscillations. The standard FACTS controllers are linear controllers which may not guarantee acceptable performance or stability in the event of a major disturbance. To overcome the drawbacks of conventional controllers, ANFIS (Adaptive Neuro-Fuzzy Inference System) control scheme has been developed in this paper, and it has been applied for the external coordinated control of series connected FACTS controllers known as Static Synchronous Series Compensators (SSSCs) employed in a two-area power system. In neuro-fuzzy control method, the simplicity of fuzzy systems and the ability of training in neural networks have been combined. The training data set the parameters of membership functions in fuzzy controller. This ANFIS can track the given input-output data in order to conform to the desired controller. Simulation studies carried out in MATLAB/SIMULINK environment demonstrate that the proposed ANFIS based SSSC controller shows the improved damping performance as compared to conventional SSSC based damping controllers under different operating conditions.

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Main Authors: Murali,D., Rajaram,M.
Format: Digital revista
Language:English
Published: Universidad Nacional Autónoma de México, Instituto de Ciencias Aplicadas y Tecnología 2013
Online Access:http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1665-64232013000600011
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spelling oai:scielo:S1665-642320130006000112014-11-12Use of ANFIS Control Approach for SSSC based Damping Controllers Applied in a Two-area Power SystemMurali,D.Rajaram,M. ANFIS FACTS low frequency electromechanical oscillations MATLAB/SIMULINK SSSC In an interconnected power system, low frequency electromechanical oscillations are initiated by normal small changes in system loads, and they become much worse following a large disturbance. Flexible AC Transmission System (FACTS) devices are widely recognized as powerful controllers for damping power system oscillations. The standard FACTS controllers are linear controllers which may not guarantee acceptable performance or stability in the event of a major disturbance. To overcome the drawbacks of conventional controllers, ANFIS (Adaptive Neuro-Fuzzy Inference System) control scheme has been developed in this paper, and it has been applied for the external coordinated control of series connected FACTS controllers known as Static Synchronous Series Compensators (SSSCs) employed in a two-area power system. In neuro-fuzzy control method, the simplicity of fuzzy systems and the ability of training in neural networks have been combined. The training data set the parameters of membership functions in fuzzy controller. This ANFIS can track the given input-output data in order to conform to the desired controller. Simulation studies carried out in MATLAB/SIMULINK environment demonstrate that the proposed ANFIS based SSSC controller shows the improved damping performance as compared to conventional SSSC based damping controllers under different operating conditions.info:eu-repo/semantics/openAccessUniversidad Nacional Autónoma de México, Instituto de Ciencias Aplicadas y TecnologíaJournal of applied research and technology v.11 n.6 20132013-01-01info:eu-repo/semantics/articletext/htmlhttp://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1665-64232013000600011en
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country México
countrycode MX
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databasecode rev-scielo-mx
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region America del Norte
libraryname SciELO
language English
format Digital
author Murali,D.
Rajaram,M.
spellingShingle Murali,D.
Rajaram,M.
Use of ANFIS Control Approach for SSSC based Damping Controllers Applied in a Two-area Power System
author_facet Murali,D.
Rajaram,M.
author_sort Murali,D.
title Use of ANFIS Control Approach for SSSC based Damping Controllers Applied in a Two-area Power System
title_short Use of ANFIS Control Approach for SSSC based Damping Controllers Applied in a Two-area Power System
title_full Use of ANFIS Control Approach for SSSC based Damping Controllers Applied in a Two-area Power System
title_fullStr Use of ANFIS Control Approach for SSSC based Damping Controllers Applied in a Two-area Power System
title_full_unstemmed Use of ANFIS Control Approach for SSSC based Damping Controllers Applied in a Two-area Power System
title_sort use of anfis control approach for sssc based damping controllers applied in a two-area power system
description In an interconnected power system, low frequency electromechanical oscillations are initiated by normal small changes in system loads, and they become much worse following a large disturbance. Flexible AC Transmission System (FACTS) devices are widely recognized as powerful controllers for damping power system oscillations. The standard FACTS controllers are linear controllers which may not guarantee acceptable performance or stability in the event of a major disturbance. To overcome the drawbacks of conventional controllers, ANFIS (Adaptive Neuro-Fuzzy Inference System) control scheme has been developed in this paper, and it has been applied for the external coordinated control of series connected FACTS controllers known as Static Synchronous Series Compensators (SSSCs) employed in a two-area power system. In neuro-fuzzy control method, the simplicity of fuzzy systems and the ability of training in neural networks have been combined. The training data set the parameters of membership functions in fuzzy controller. This ANFIS can track the given input-output data in order to conform to the desired controller. Simulation studies carried out in MATLAB/SIMULINK environment demonstrate that the proposed ANFIS based SSSC controller shows the improved damping performance as compared to conventional SSSC based damping controllers under different operating conditions.
publisher Universidad Nacional Autónoma de México, Instituto de Ciencias Aplicadas y Tecnología
publishDate 2013
url http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1665-64232013000600011
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