An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm

In this study, an optimal meta-heuristic optimization algorithm for load frequency control (LFC) is utilized in two-area power systems. This meta-heuristic algorithm is called harmony search (HS), it is used to tune PI controller parameters (Kp, Kt) automatically. The developed controller (HS-PI) wi...

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Main Authors: Najeeb, M., Mansor, M., Feyad, H., Taha, E., Abdullah, G.
Format: Article
Language:en_US
Published: 2017
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spelling my.uniten.dspace-59212018-01-18T02:26:46Z An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm Najeeb, M. Mansor, M. Feyad, H. Taha, E. Abdullah, G. In this study, an optimal meta-heuristic optimization algorithm for load frequency control (LFC) is utilized in two-area power systems. This meta-heuristic algorithm is called harmony search (HS), it is used to tune PI controller parameters (Kp, Kt) automatically. The developed controller (HS-PI) with LFC loop is very important to minimize the system frequency and keep the system power is maintained at scheduled values under sudden loads changes. Integral absolute error (IAE) is used as an objective function to enhance the overall system performance in terms of settling time, maximum deviation, and peak time. The two-area power systems and developed controller are modelled using MATLAB software (Simulink/Code). As a result, the developed control algorithm (HS-PI) is more robustness and efficient as compared to PSO-PI control algorithm under same operation conditions. Copyright © 2017 Institute of Advanced Engineering and Science. All rights reserved. 2017-12-08T07:41:14Z 2017-12-08T07:41:14Z 2017 Article 10.11591/ijece.v7i6.pp3217-3225 en_US An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm. International Journal of Electrical and Computer Engineering, 7(6), 3217-3225.
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language en_US
description In this study, an optimal meta-heuristic optimization algorithm for load frequency control (LFC) is utilized in two-area power systems. This meta-heuristic algorithm is called harmony search (HS), it is used to tune PI controller parameters (Kp, Kt) automatically. The developed controller (HS-PI) with LFC loop is very important to minimize the system frequency and keep the system power is maintained at scheduled values under sudden loads changes. Integral absolute error (IAE) is used as an objective function to enhance the overall system performance in terms of settling time, maximum deviation, and peak time. The two-area power systems and developed controller are modelled using MATLAB software (Simulink/Code). As a result, the developed control algorithm (HS-PI) is more robustness and efficient as compared to PSO-PI control algorithm under same operation conditions. Copyright © 2017 Institute of Advanced Engineering and Science. All rights reserved.
format Article
author Najeeb, M.
Mansor, M.
Feyad, H.
Taha, E.
Abdullah, G.
spellingShingle Najeeb, M.
Mansor, M.
Feyad, H.
Taha, E.
Abdullah, G.
An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm
author_facet Najeeb, M.
Mansor, M.
Feyad, H.
Taha, E.
Abdullah, G.
author_sort Najeeb, M.
title An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm
title_short An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm
title_full An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm
title_fullStr An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm
title_full_unstemmed An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm
title_sort optimal lfc in two-area power systems using a meta-heuristic optimization algorithm
publishDate 2017
_version_ 1644493800211480576
score 13.214268