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PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Application of the Voltage Control Technique and MPPT of Stand-alone PV System with Storage, HIVZIEFENDIC, J., VUIC, L., LALE, S., SARIC, M.
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 HIGH-IMPACT PAPER 

Solution Approach to Automatic Generation Control Problem Using Hybridized Gravitational Search Algorithm Optimized PID and FOPID Controllers

DAHIYA, P. See more information about DAHIYA, P. on SCOPUS See more information about DAHIYA, P. on IEEExplore See more information about DAHIYA, P. on Web of Science, SHARMA, V. See more information about  SHARMA, V. on SCOPUS See more information about  SHARMA, V. on SCOPUS See more information about SHARMA, V. on Web of Science, NARESH, R. See more information about NARESH, R. on SCOPUS See more information about NARESH, R. on SCOPUS See more information about NARESH, R. on Web of Science
 
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Download PDF pdficon (1,083 KB) | Citation | Downloads: 1,057 | Views: 4,390

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
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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.


References | Cited By

Cited-By Clarivate Web of Science

Web of Science® Times Cited: 19 [View]
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Cited-By SCOPUS

SCOPUS® Times Cited: 24
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Cited-By CrossRef

[1] A Novel Optimal Combined Fuzzy PID Controller Employing Dragonfly Algorithm for Solving Automatic Generation Control Problem, Kouba, Nour EL Yakine, Menaa, Mohamed, Hasni, Mourad, Boudour, Mohamed, Electric Power Components and Systems, ISSN 1532-5008, Issue 19-20, Volume 46, 2018.
Digital Object Identifier: 10.1080/15325008.2018.1533604
[CrossRef]

[2] A review on fractional order (FO) controllers’ optimization for load frequency stabilization in power networks, Latif, Abdul, Hussain, S.M. Suhail, Das, Dulal Chandra, Ustun, Taha Selim, Iqbal, Atif, Energy Reports, ISSN 2352-4847, Issue , 2021.
Digital Object Identifier: 10.1016/j.egyr.2021.06.088
[CrossRef]

[3] AGC of restructured multi-area multi-source hydrothermal power systems incorporating energy storage units via optimal fractional-order fuzzy PID controller, Arya, Yogendra, Neural Computing and Applications, ISSN 0941-0643, Issue 3, Volume 31, 2019.
Digital Object Identifier: 10.1007/s00521-017-3114-5
[CrossRef]

[4] Automatic generation control using disrupted oppositional based gravitational search algorithm optimised sliding mode controller under deregulated environment, Dahiya, Preeti, Sharma, Veena, Naresh, Ram, IET Generation, Transmission & Distribution, ISSN 1751-8695, Issue 16, Volume 10, 2016.
Digital Object Identifier: 10.1049/iet-gtd.2016.0175
[CrossRef]

[5] Comparative performance analysis of 2DOF state feedback controller for automatic generation control using whale optimization algorithm, Simhadri, Kumara Swamy, Mohanty, Banaja, Panda, Sanjaya Kumar, Optimal Control Applications and Methods, ISSN 0143-2087, Issue 1, Volume 40, 2019.
Digital Object Identifier: 10.1002/oca.2462
[CrossRef]

[6] Optimal sliding mode control for frequency regulation in deregulated power systems with DFIG-based wind turbine and TCSC–SMES, Dahiya, Preeti, Sharma, Veena, Naresh, R., Neural Computing and Applications, ISSN 0941-0643, Issue 7, Volume 31, 2019.
Digital Object Identifier: 10.1007/s00521-017-3250-y
[CrossRef]

[7] Model Predictive Controller-Based Voltage and Frequency Regulation in Renewable Energy Integrated Power System Coordinated with Virtual Inertia and Redox Flow Battery, Kumar, Vineet, Sharma, Veena, Naresh, R., Iranian Journal of Science and Technology, Transactions of Electrical Engineering, ISSN 2228-6179, Issue 1, Volume 47, 2023.
Digital Object Identifier: 10.1007/s40998-022-00561-x
[CrossRef]

[8] Stochastic wind energy integrated multi source power system control via a novel model predictive controller based on Harris Hawks optimization, Kumar, Vineet, Sharma, Veena, Arya, Yogendra, Naresh, R., Singh, Amita, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, ISSN 1556-7036, Issue 4, Volume 44, 2022.
Digital Object Identifier: 10.1080/15567036.2022.2156637
[CrossRef]

[9] Hybridized gravitational search algorithm tuned sliding mode controller design for load frequency control system with doubly fed induction generator wind turbine, Dahiya, Preeti, Sharma, Veena, Naresh, R., Optimal Control Applications and Methods, ISSN 0143-2087, Issue 6, Volume 38, 2017.
Digital Object Identifier: 10.1002/oca.2305
[CrossRef]

[10] Energy-efficient clustering method for wireless sensor networks using modified gravitational search algorithm, Ebrahimi Mood, Sepehr, Javidi, Mohammad Masoud, Evolving Systems, ISSN 1868-6478, Issue 4, Volume 11, 2020.
Digital Object Identifier: 10.1007/s12530-019-09264-x
[CrossRef]

[11] A Novel Hybrid IGSA-BPSO Optimized FOPID Controller for Load Frequency Control of Multi-source Restructured Power System, Kumar, Ajay, Gupta, Deepak Kumar, Ghatak, Sriparna Roy, Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering), ISSN 2352-0965, Issue 7, Volume 16, 2023.
Digital Object Identifier: 10.2174/2352096516666230427122716
[CrossRef]

[12] Combined load frequency and terminal voltage control of power systems using moth flame optimization algorithm, Lal, Deepak Kumar, Barisal, Ajit Kumar, Journal of Electrical Systems and Information Technology, ISSN 2314-7172, Issue 1, Volume 6, 2019.
Digital Object Identifier: 10.1186/s43067-019-0010-3
[CrossRef]

[13] 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.
Digital Object Identifier: 10.1007/s00500-020-05215-w
[CrossRef]

[14] CLSA-MRPID controller for automatic generation control of a three-area hybrid system, Acharyulu, B. V. S., Hota, Prakash Kumar, Mohanty, Banaja, Energy Systems, ISSN 1868-3967, Issue 1, Volume 11, 2020.
Digital Object Identifier: 10.1007/s12667-018-0305-9
[CrossRef]

[15] Salp swarm algorithm-based model predictive controller for frequency regulation of solar integrated power system, Singh, Amita, Sharma, Veena, Neural Computing and Applications, ISSN 0941-0643, Issue 12, Volume 31, 2019.
Digital Object Identifier: 10.1007/s00521-019-04422-3
[CrossRef]

[16] Automatic generation control using disrupted gravitational search algorithm based proportional integral derivative controller, Preeti, , Sharma, Veena, Naresh, R., Pulluri, Harish, 2015 2nd International Conference on Recent Advances in Engineering & Computational Sciences (RAECS), ISBN 978-1-4673-8253-3, 2015.
Digital Object Identifier: 10.1109/RAECS.2015.7453317
[CrossRef]

[17] Automatic generation control of multi-source interconnected power system including DFIG wind turbine, Preeti, , Sharma, Veena, Naresh, R., Pulluri, Harish, 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), ISBN 978-1-4673-8587-9, 2016.
Digital Object Identifier: 10.1109/ICPEICES.2016.7853204
[CrossRef]

[18] AGC of a two area nonlinear power system using BOA optimized FOPID+PI multistage controller, Lal, Deepak Kumar, Barisal, Ajit, Madasu, Satya Dinesh, 2019 Second International Conference on Advanced Computational and Communication Paradigms (ICACCP), ISBN 978-1-5386-7989-0, 2019.
Digital Object Identifier: 10.1109/ICACCP.2019.8882976
[CrossRef]

[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.
Digital Object Identifier: 10.1109/ICERA53111.2021.9538646
[CrossRef]

[20] Load Frequency Control of Two Area Interconnected Power System Using Fuzzy Logic Control and PID Controller, Tur, Mehmet Rida, Wadi, Mohammed, Shobole, Abdulfetah, Ay, Selim, 2018 7th International Conference on Renewable Energy Research and Applications (ICRERA), ISBN 978-1-5386-5982-3, 2018.
Digital Object Identifier: 10.1109/ICRERA.2018.8566890
[CrossRef]

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