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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
Current issue: Aug 2017
Next issue: Nov 2017
Avg review time: 77 days


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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FEATURED ARTICLE

Wind Speed Prediction with Wavelet Time Series Based on Lorenz Disturbance, ZHANG, Y., WANG, P., CHENG, P., LEI, S.
Issue 3/2017

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LATEST NEWS

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
We have the confirmation Advances in Electrical and Computer Engineering will be included in the EBSCO database.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

2017-Jan-30
We have the confirmation Advances in Electrical and Computer Engineering will be included in the Gale database.

2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

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  2/2015 - 4

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
 
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,083 KB) | Citation | Downloads: 432 | Views: 1,498

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 ISI Web of Science

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Cited-By CrossRef

SCOPUS® Times Cited: 3
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Cited-By CrossRef

[1] 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, 2017.
Digital Object Identifier: 10.1002/oca.2305
[CrossRef]

[2] 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]

[3] 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]

[4] 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]

[5] 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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Copyright ©2001-2017
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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