Optimization of Solar Panel Output Using a Camera-Based Solar Tracker Raspberry Pi Integrated

  • Siti Suci Murni Universitas Negeri Semarang
  • Noor Hudallah Universitas Negeri Semarang
  • Tatyantoro Andrasto Universitas Negeri Semarang
  • Cahyo Fajar Adhiningtyas Universitas Negeri Semarang
  • Seftriana Anifa Khusniasari Universitas Negeri Semarang


Maximum output from the operation of solar cell depends on the temperature of the solar cell, solar radiation, wind speed, the state of the earth's atmosphere, the orientation of the solar cell and the position of the location of the solar cell against the sun (tilt angle). Solar Tracker is a device that automatically change the orientation of a solar panel towards the position of the sun and increasing the insolation. Initially the solar tracker is set up using LDR then image processing-based settings can reduce tracking errors. Image-based solar tracker still uses a full-sized computer that requires a lot of energy and space. This research aims to improve the accuracy of the direction of the solar panel and optimize the output of the solar panel by increasing the angle of solar radiation (insolation) using the Solar Tracker with a camera sensor and a Raspberry Pi minicomputer. The use of cameras is intended to reduce errors from LDR-based systems and the use of Raspberry Pi replaces full-sized computer. The method to track position of the sun is by tracking the pixel with highest value. From the output analysis the solar panel proved to be optimized by the application of Raspberry Pi-integrated camera solar tracker. The comparison of the output power between the stationary solar panel and the solar panel installed on the Raspberry Pi-integrated camera solar tracker is 1: 1,389 (21,5487W: 29,8822W) in the no-load test and 1: 1,2042 (6,0344W: 7, 2671W) in tests with a 12V-5W bulb load.


C. Philibert, Solar Energy Perspective, Paris: International Energy Agency, 2011.

Z. El Kadmiri, O. El Kadmiri, L. Masmoudi, dan M.N. Bargach, “A Novel Solar Tracker Based on Omnidirectional Computer Vision,” Journal of Solar Energy, Vol. 2015, hal. 1-6, 2015.

T. Tudorache dan L. Kreindler, “Design of a Solar Tracker System for PV Power Plants,” Acta Polytechnica Hungarica, Vol. 7, No. 1, hal. 23-39, 2015.

K. Azizi dan A. Ghaffari, “Design and Manufacturing of a High-Precision Sun Tracking System Based on Image Processing,” International Journal of Photoenergy, Vol. 2013, hal. 1-7, 2013.

(2020) Raspberry Pi Foundation, [Online], https://www.raspberrypi.org/, tanggal akses 2-jan-2021.

Sugiyono, Metode Penelitian Kuantitatif Kualitatif dan R&D, Bandung, Indonesia: Alfabeta, 2017.

M.K. Iqbal, T. Islam, M. Chowdhury, dan A. Imteaj, “Construction of Single Axis Automatic Solar Tracking System,” International Journal of u- and e- Service, Science and Technology, Vol. 8, No. 1, hal. 389-400, 2015.

P.M. Kannan, Raja TE, dan R. Gowtham, “Real-time Solar Energy Optimization Systems,” Open Access Scientific Reports, Vol 2, No. 4, hal. 712-714, 2013.

W. Purwanto, “Rancang Bangun Penggerak Panel Surya Dual Axis Berbasis Mikrokontroler Atmega 328,” Skripsi, Universitas Negeri Semarang, Semarang, Indonesia, 2017.

J.-M. Wang dan C.-L. Lu, “Design and Implementation of a Sun Tracker with a Dual-Axis Single Motor for an Optical Sensor-Based Photovoltaic System,” Sensors, Vol. 13, No. 3, pp. 3157-3168, 2013.

“IRF3205 datasheet,” International Rectifier, California, USA.

“IRF9540N datasheet,” International Rectifier, California, USA.

How to Cite
Siti Suci Murni, Noor Hudallah, Tatyantoro Andrasto, Cahyo Fajar Adhiningtyas, & Seftriana Anifa Khusniasari. (2021). Optimization of Solar Panel Output Using a Camera-Based Solar Tracker Raspberry Pi Integrated. Jurnal Nasional Teknik Elektro Dan Teknologi Informasi, 10(3), 282-290. https://doi.org/10.22146/jnteti.v10i3.1142