Key points are not available for this paper at this time.
Climate change, global warming, and rising fossil fuel pose significant challenges in present days across worldwide. To combat these issues, governments and organizations are promoting renewable energy sources, such as solar power, which converts sunlight into electricity or thermal energy. In the current scenario, static-oriented Photovoltaic (PV) panels are hampered by fluctuations in the sun's trajectory, leading to suboptimal solar energy conversion. To address these issues, this manuscript proposes a low-cost prototype of a two-axis solar tracker that integrates four optical sensor modules as feedback sensors and two direct current geared motors to maximize solar energy harvesting. Comparative analysis between a fixed-oriented PV panel and the solar tracker, using conventional on–off and artificial intelligence-based fuzzy logic control methods, verifies the two-axis solar tracker's performance. The fuzzy logic controller-based solar tracker net energy gains approximately 14.2% more power than the fixed-oriented PV panel daily and boasts an average tracking error of 0.29°, indicating its reliability.
Sanyal et al. (Mon,) studied this question.