Flocking-Inspired Solar Tracking System with Adaptive Performance in Varied Environmental Conditions

Khadidja Dahli, Adrian Ilinca (), Abdellah Benallal (), Nawal Cheggaga and Tayeb Allaoui
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Khadidja Dahli: Department of Automatic and Electrical Engineering, Faculty of Technology, University of Blida 1, Blida 09000, Algeria
Adrian Ilinca: Department of Mechanical Engineering, École de Technologie Supérieure, Montréal, QC H3C 1K3, Canada
Abdellah Benallal: Engineering Department, Université du Québec à Rimouski, Rimouski, QC G5L 3A1, Canada
Nawal Cheggaga: Electrical and Remote Control Systems Laboratory, LabSET, Faculty of Technology, University of Blida 1, Blida 09000, Algeria
Tayeb Allaoui: Electrical Engineering Department, Faculty of Science and Technology, University of Ibn Khaldoun Tiaret, Tiaret 14000, Algeria

Energies, 2025, vol. 18, issue 8, 1-18

Abstract: Traditional solar trackers are designed to follow the sun’s exact position, assuming that perfect sun alignment always results in optimal energy generation. However, despite perfect alignment, external factors such as shading, dust, and wind can reduce power output in real-world conditions. To address these challenges, our novel system draws inspiration from the flocking behavior of birds, where individual entities adjust their behavior based on their energy output and the energy outputs of neighboring panels. The system uses Particle Swarm Optimization (PSO) to mimic this behavior, dynamically adjusting the solar tracker’s position to respond to varying environmental conditions. One key innovation is introducing a power threshold strategy, set between 1.5 W and 2 W, to avoid continuous tracker movement and conserve energy by minimizing unnecessary adjustments when the power difference is insignificant. The proposed system demonstrated an impressive 8% increase in energy gain and a reduction of up to 11% in energy consumption compared to the traditional continuous tracker. The tracking accuracy improved by 84%, with the mean tracking error reduced in the range of 0.78° to 1.09°. The system also captured 17.4% more solar irradiance, showcasing its superior efficiency. Despite environmental challenges such as dust and shading, the proposed system consistently outperformed the traditional tracker regarding energy savings and overall performance, offering a more resilient and energy-efficient solution for solar energy generation.

Keywords: bird flocking behavior; particle swarm optimization (PSO); power threshold; solar energy; solar trackers (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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