- The effectiveness of photovoltaic (PV) energy systems is greatly reliant on the capability to optimally follow the path of the sun during the entire day. A common practice in automatic sun tracking systems is to use fixed timetables or generalized heuristics which do not consider local solar weather and capture even less energy. This study suggests a new approach in designing sun tracking devices using Local Solar Time (LST) for optimization of panel repositioning. The system is able to incorporate LST into the tracking mechanism so that PV panels can better track the sun's true position with account for location, season, and timezone shifts. The model proposed combines priori astronomic databases with real-time data from the environment in order to constantly update the solar panels’ azimuth and elevation angles. A prototype was built for practical verification along with a detailed simulation environment to evaluate the system's performance under diverse geographic and climatic conditions. Both simulations and field experiments proved that the new energy capture mechanism with LST incorporation can significantly improve power output, gaining between 15% and 25% more energy than systems with no tracking, and up to 10% more than conventional dual-axis trackers. Moreover, the LST based system has higher accuracy with minimal sensors compared to sophisticated structures which makes it more cost-efficient and easier to deploy. This research aids in perfecting the intelligent solar tracking systems and underscores the importance of the time and place selection for optimization in the renewable energy system's production. The results of this study indicate that the trackers based on LST could practically and feasibly improve the collection of solar energy and as a result, assist to the efforts made toward sustainable and decentralized energy sources worldwide.
 

Local Solar Time, photovoltaic systems, solar tracking, energy optimization