The comparison of dual axis photovoltaic tracking system using artificial intelligence techniques

Ali, Machrus and Firdaus, Aji Akbar and Arof, Hamzah and Nurohmah, Hidayatul and Suyono, Hadi and Putra, Dimas Fajar Uman and Muslim, Muhammad Aziz (2021) The comparison of dual axis photovoltaic tracking system using artificial intelligence techniques. IAES International Journal of Artificial Intelligence, 10 (4). pp. 901-909. ISSN 20894872, DOI

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In this paper, the efficiency of photovoltaic panels is improved by adding a sun tracking system. The solar tracking system is used for tracking the sun so that photovoltaic always faces the sun. This system uses a dual axis consisting of horizontal rotation axis and a vertical rotation axis. The horizontal rotational axis motion is to follow the azimuth angle of the sun from north to south. Then, to follow the sun's azimuth angle from east to west is the vertical axis motion. Both types of movements are controlled using a PID controller that is optimized with an artificial intelligence approach, namely particle swarm optimization (PID-PSO), firefly algorithm (PID-FA), imperialist competitive algorithm (PID-ICA), bat algorithm (PID-BA), and ant colony optimization (PID-ACO). Experiments of various approaches were carried out and the corresponding performance compared. The experimental results show that PID-BA performs best in terms of settling time and overshoot. The results also allow the comparison of different PID controller and the calculation of the fastest completion time. © 2021, Institute of Advanced Engineering and Science. All rights reserved.

Item Type: Article
Funders: Ministry of Education and Culture of the Republic of Indonesia
Uncontrolled Keywords: Bat algorithm; Dual axis photovoltaic tracking system; PID controller
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering > Department of Electrical Engineering
Depositing User: Ms Zaharah Ramly
Date Deposited: 27 Nov 2023 07:15
Last Modified: 27 Nov 2023 07:15

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