An intelligent coordinator design for GCSC and AGC in a two-area hybrid power system

This study addresses the design procedure of an optimized fuzzy fine-tuning (OFFT) approach as an intelligent coordinator for gate controlled series capacitors (GCSC) and automatic generation control (AGC) in hybrid multi-area power system. To do so, a detailed mathematical formulation for the parti...

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Main Authors: Khezri, R., Oshnoei, A., Oshnoei, S., Bevrani, H., Muyeen, S.M.
Format: Journal Article
Published: Elsevier BV 2019
Online Access:http://hdl.handle.net/20.500.11937/74915
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author Khezri, R.
Oshnoei, A.
Oshnoei, S.
Bevrani, H.
Muyeen, S.M.
author_facet Khezri, R.
Oshnoei, A.
Oshnoei, S.
Bevrani, H.
Muyeen, S.M.
author_sort Khezri, R.
building Curtin Institutional Repository
collection Online Access
description This study addresses the design procedure of an optimized fuzzy fine-tuning (OFFT) approach as an intelligent coordinator for gate controlled series capacitors (GCSC) and automatic generation control (AGC) in hybrid multi-area power system. To do so, a detailed mathematical formulation for the participation of GCSC in tie-line power flow exchange is presented. The proposed OFFT approach is intended for valid adjustment of proportional–integral controller gains in GCSC structure and integral gain of secondary control loop in the AGC structure. Unlike the conventional classic controllers with constant gains that are generally designed for fixed operating conditions, the outlined approach demonstrates robust performance in load disturbances with adapting the gains of classic controllers. The parameters are adjusted in an online manner via the fuzzy logic method in which the sine cosine algorithm subjoined to optimize the fuzzy logic. To prove the scalability of the proposed approach, the design has also been implemented on a hybrid interconnected two-area power system with nonlinearity effect of governor dead band and generation rate constraint. Success of the proposed OFFT approach is established in three scenarios by comparing the dynamic performance of concerned power system with several optimization algorithms including artificial bee colony algorithm, genetic algorithm, improved particle swarm optimization algorithm, ant colony optimization algorithm and sine cosine algorithm.
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format Journal Article
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T11:02:59Z
publishDate 2019
publisher Elsevier BV
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spelling curtin-20.500.11937-749152021-11-09T07:14:00Z An intelligent coordinator design for GCSC and AGC in a two-area hybrid power system Khezri, R. Oshnoei, A. Oshnoei, S. Bevrani, H. Muyeen, S.M. This study addresses the design procedure of an optimized fuzzy fine-tuning (OFFT) approach as an intelligent coordinator for gate controlled series capacitors (GCSC) and automatic generation control (AGC) in hybrid multi-area power system. To do so, a detailed mathematical formulation for the participation of GCSC in tie-line power flow exchange is presented. The proposed OFFT approach is intended for valid adjustment of proportional–integral controller gains in GCSC structure and integral gain of secondary control loop in the AGC structure. Unlike the conventional classic controllers with constant gains that are generally designed for fixed operating conditions, the outlined approach demonstrates robust performance in load disturbances with adapting the gains of classic controllers. The parameters are adjusted in an online manner via the fuzzy logic method in which the sine cosine algorithm subjoined to optimize the fuzzy logic. To prove the scalability of the proposed approach, the design has also been implemented on a hybrid interconnected two-area power system with nonlinearity effect of governor dead band and generation rate constraint. Success of the proposed OFFT approach is established in three scenarios by comparing the dynamic performance of concerned power system with several optimization algorithms including artificial bee colony algorithm, genetic algorithm, improved particle swarm optimization algorithm, ant colony optimization algorithm and sine cosine algorithm. 2019 Journal Article http://hdl.handle.net/20.500.11937/74915 10.1016/j.asoc.2018.12.026 Elsevier BV fulltext
spellingShingle Khezri, R.
Oshnoei, A.
Oshnoei, S.
Bevrani, H.
Muyeen, S.M.
An intelligent coordinator design for GCSC and AGC in a two-area hybrid power system
title An intelligent coordinator design for GCSC and AGC in a two-area hybrid power system
title_full An intelligent coordinator design for GCSC and AGC in a two-area hybrid power system
title_fullStr An intelligent coordinator design for GCSC and AGC in a two-area hybrid power system
title_full_unstemmed An intelligent coordinator design for GCSC and AGC in a two-area hybrid power system
title_short An intelligent coordinator design for GCSC and AGC in a two-area hybrid power system
title_sort intelligent coordinator design for gcsc and agc in a two-area hybrid power system
url http://hdl.handle.net/20.500.11937/74915