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

Machrus Ali, Aji Akbar Firdaus, Hamzah Arof, Hidayatul Nurohmah, Hadi Suyono, Dimas Fajar Uman Putra, Muhammad Aziz Muslim

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)901-909
Number of pages9
JournalIAES International Journal of Artificial Intelligence
Volume10
Issue number4
DOIs
Publication statusPublished - 1 Dec 2021

Keywords

  • Bat algorithm
  • Dual axis photovoltaic tracking system
  • PID controller

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