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Solution Approach to Automatic Generation Control Problem Using Hybridized Gravitational Search Algorithm Optimized PID and FOPID ControllersDAHIYA, P.   , SHARMA, V. , NARESH, R. |
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Author keywords
automatic generation control, disruption operator, fractional calculus, gravitational search algorithm, opposition based learning
References keywords
power(21), control(17), load(9), frequency(9), algorithm(9), generation(8), systems(7), automatic(7), system(6), search(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2015-05-31
Volume 15, Issue 2, Year 2015, On page(s): 23 - 34
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.02004
Web of Science Accession Number: 000356808900004
SCOPUS ID: 84979725893
Abstract
This paper presents the application of hybrid opposition based disruption operator in gravitational search algorithm (DOGSA) to solve automatic generation control (AGC) problem of four area hydro-thermal-gas interconnected power system. The proposed DOGSA approach combines the advantages of opposition based learning which enhances the speed of convergence and disruption operator which has the ability to further explore and exploit the search space of standard gravitational search algorithm (GSA). The addition of these two concepts to GSA increases its flexibility for solving the complex optimization problems. This paper addresses the design and performance analysis of DOGSA based proportional integral derivative (PID) and fractional order proportional integral derivative (FOPID) controllers for automatic generation control problem. The proposed approaches are demonstrated by comparing the results with the standard GSA, opposition learning based GSA (OGSA) and disruption based GSA (DGSA). The sensitivity analysis is also carried out to study the robustness of DOGSA tuned controllers in order to accommodate variations in operating load conditions, tie-line synchronizing coefficient, time constants of governor and turbine. Further, the approaches are extended to a more realistic power system model by considering the physical constraints such as thermal turbine generation rate constraint, speed governor dead band and time delay. |
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[16] Design of new fractional order PI–fractional order PD cascade controller through dragonfly search algorithm for advanced load frequency control of power systems, Çelik, Emre, Soft Computing, ISSN 1432-7643, Issue 2, Volume 25, 2021.
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[19] Cascade of Fractional Order PID based PSO Algorithm for LFC in Two-Area Power System, Shouran, Mokhtar, Alsseid, Aleisawee M., 2021 3rd International Conference on Electronics Representation and Algorithm (ICERA), ISBN 978-1-6654-3398-3, 2021.
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
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