Focused Time Delay Neural Network For Tuning Automatic Voltage Regulator
This paper proposes a novel controller for automatic voltage regulator (AVR) system. The controller is used Focused Time Delay Neural Network (FTDNN). It does not require dynamic backpropagation to compute the network gradient. FTDNN AVR can train network faster than other dynamic networks. Simulation was performed to compare load angle (load angle) and Speed. The performance of the system with FTDNN-AVR has compared with a Conventional AVR (C-AVR) and RNN AVR. Simulations in Matlab/Simulink show the effectiveness of FTDNN-AVR design, and superior robust performance with different cases.
Yavarian, K., Hashemi, F.,Mohammadian,A.. Design of Intelligent PID Controller for AVR System Using an Adaptive Neuro Fuzzy Inference System. International Journal of Electrical and Computer Engineering (IJECE), 4(5), pp 703-718, 2014.
Salim M. El Sharif Abdalla, Comparative Study Of Excitation System, AVR, And PSS Models For Synchronous Generator Under The Phase To Ground Fault. Masterâ€™s Thesis, , Near East University. 2015
Tang, B. Parameter tuning and experimental results of power system stabilizer. Masterâ€™s Thesis, Louisiana State University. 2011
Aribowo, W. An Adaptive Power System Stabilizer Based On Focused Time Delay Neural Network. Teknosains, 7(1), 2017, pp 67-73. http://dx.doi.org/10.22146/teknosains.35130
Mustafa M. Abed, A. El-Shafie, Siti Aminah Bt. Osman. Creep Predicting Model in Masonry Structure Utilizing Dynamic Neural Network. Journal of Computer Science 6 (5), pp : 597-605, 2010
MATLAB 7.6.0 (R2008a) neural network Toolbox software
D. K. Sambariyaa, Rajendra Prasad. Routh Stability Array Method Based Reduced Model of Single Machine Infinite Bus with Power System Stabilizer. Proceedings of International Conference on Emerging Trends in Electrical, Communication and Information Technologies (ICECIT-2012), Andhrapradesh, India, pp 27-34, Desember 2012.
B. Zaker, G. B. Gharehpetian, N. Moaddabi. Parameter Identification of Heffron-Phillips Model Considering AVR Using On-Line Measurements Data. Proceedings of International Conference on Renewable Energies and Power Quality(ICREPQâ€™14),Cordoba,Spain,April 2014.
Kharrazi, A. Artificial Neural Network Based Power System Stabilizer on a Single Machine Infinite Bus System Modelled in Digsilent Powerfactory and Matlab. Electrical Engineering: An International Journal (EEIJ), 2, pp 1-11, 2015.
Copyright (c) 2019 EMITTER International Journal of Engineering Technology
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The copyright to this article is transferred to Politeknik Elektronika Negeri Surabaya(PENS) if and when the article is accepted for publication. The undersigned hereby transfers any and all rights in and to the paper including without limitation all copyrights to PENS. The undersigned hereby represents and warrants that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required. The undersigned represents that he/she has the power and authority to make and execute this assignment. The copyright transfer form can be downloaded here .
The corresponding author signs for and accepts responsibility for releasing this material on behalf of any and all co-authors. This agreement is to be signed by at least one of the authors who have obtained the assent of the co-author(s) where applicable. After submission of this agreement signed by the corresponding author, changes of authorship or in the order of the authors listed will not be accepted.
Plagiarism screening will be conducted by EMITTER Journal Editorial Board using iThenticate Plagiarism Checker and CrossCheck plagiarism screening service. Author should download and signing declaration of plagiarism form here and resubmit it with copyright transfer form via online submission.