An Improved Feed-Forward Backpropagation Neural Network Based on Marine Predators Algorithm for Tuning Automatic Voltage Regulator

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Published: Jun 27, 2023
DOI: https://doi.org/10.37936/ecti-eec.2023212.249830
Keywords:
Marine predators algorithm feed-forward backpropagation neural network automatic voltage regulator metaheuristic; power system

Main Article Content

Widi Aribowo
Department of Electrical Engineering, Universitas Negeri Surabaya, Indonesia.
Reza Rahmadian
Department of Electrical Engineering, Universitas Negeri Surabaya, Indonesia.
Mahendra Widyartono
Department of Electrical Engineering, Universitas Negeri Surabaya, Indonesia.
Lukita
Department of Electrical Engineering, Universitas Negeri Surabaya, Indonesia.
Aditya Prapanca
Department of Computer Engineering, Universitas Negeri Surabaya, Indonesia.

Abstract

This research will discuss the application of an automatic voltage regulator based on the feed-forward back propagation neural network (FFBNN), which is enhanced by the marine predator algorithm (MPA). The marine predators algorithm is a method that adopts marine ecosystem life that is identified in the relationship between predators and prey. MPA is adopting a natural approach to arranging the best food search strategies and finding the latest strategy. The focus of the research is on the performance of speed and rotor angle. The performance of the proposed method will be tested using hidden layer variations. In addition, the proposed method will be compared with the feed-forward backpropagation neural network (FFBNN), cascade-forward backpropagation neural network (CFBNN), Elman recurrent neural network (E-RNN), and Focused Time Delay neural network (FTDNN). The speed and rotor angle of the proposed method have good values. The MPA-FFBNN results are not much different from other methods. The experimental results show that the performance of the proposed method has promising results.

Article Details

How to Cite
Aribowo, W., Rahmadian, R., Widyartono, M., Wardani, A., & Prapanca, A. (2023). An Improved Feed-Forward Backpropagation Neural Network Based on Marine Predators Algorithm for Tuning Automatic Voltage Regulator. ECTI Transactions on Electrical Engineering, Electronics, and Communications, 21(2), 249830 . https://doi.org/10.37936/ecti-eec.2023212.249830
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Vol. 21 No. 2 (2023): Regular Issue (June 2023)
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Author Biographies

Widi Aribowo, Department of Electrical Engineering, Universitas Negeri Surabaya, Indonesia.

Widi Aribowo is a lecturer in the Department of Electrical Engineering, Universitas
Negeri Surabaya, Indonesia. He is B.Sc in Power Engineering/ Sepuluh Nopember Institute of Technology (ITS) - Surabaya in 2005. He is M.Eng in Power Engineering/ Sepuluh Nopember Institute of Technology (ITS) – Surabaya in 2009. He is mainly research inthe power system and control.

Reza Rahmadian, Department of Electrical Engineering, Universitas Negeri Surabaya, Indonesia.

Reza Rahmadian received his Bachelor of Applied Science from Electronic Engineering
Polytechnic Institute of Surabaya (PENS), Surabaya, Indonesia, in 2006, and his Master
of Engineering Science from Curtin University, Australia, in 2013. He is currently a lecturer at the Department of Electrical Engineering, Universitas Negeri Surabaya,
Indonesia. His research interests include renewable energy.

Mahendra Widyartono, Department of Electrical Engineering, Universitas Negeri Surabaya, Indonesia.

Mahendra Widyartono received his Bachelor of Engineering from Sepuluh Nopember
Institute of Technology (ITS), Surabaya, Indonesia, in 2006, and his Master of Engineering from Brawijaya University, Indonesia, in 2012. He is currently a lecturer at the Department of Electrical Engineering, Universitas Negeri Surabaya, Indonesia. His research interests include power system and renewable energy.

Lukita, Department of Electrical Engineering, Universitas Negeri Surabaya, Indonesia.

Ayusta Lukita Wardani received her Bachelor of Applied Science from Electronic Engineering Polytechnic Institute of Surabaya (PENS), Surabaya, Indonesia, in 2011, and her Master of Engineering from Sepuluh Nopember Institute of Technology (ITS), Indonesia, in 2017. She is currently a lecturer at the Department of Electrical Engineering, Universitas Negeri Surabaya, Indonesia. Her research interests include renewable energy.

Aditya Prapanca, Department of Computer Engineering, Universitas Negeri Surabaya, Indonesia.

Aditya Prapanca received his Bachelor of Engineering from Sepuluh Nopember Institute of Technology (ITS), Surabaya, Indonesia, in 2000, and his Master of Computer from Sepuluh Nopember Institute of Technology (ITS), Indonesia, in 2007. He is currently a lecturer at the Department of Computer Engineering, Universitas Negeri Surabaya, Indonesia. His research interests include artificial intelligence

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