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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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automatic generation control, disruption operator, fractional calculus, gravitational search algorithm, opposition based learning
power(21), control(17), load(9), frequency(9), algorithm(9), generation(8), systems(7), automatic(7), system(6), search(5)
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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
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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 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, 2017.
Digital Object Identifier: 10.1007/s00521-017-3250-y [CrossRef]
 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]
 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, 2017.
Digital Object Identifier: 10.1007/s00521-017-3114-5 [CrossRef]
 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 1751-8687, Issue 16, Volume 10, 2016.
Digital Object Identifier: 10.1049/iet-gtd.2016.0175 [CrossRef]
 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]
 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]
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Stefan cel Mare University of Suceava, Romania
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