DESIGN AND CONSTRUCTION OF DUAL-AXIS SOLAR TRACKER

ABSTRACT The need for more efficient solar energy systems has increased due to the growing global demand for renewable fuels. This research studies the development, implementation, and operational assessment of a photovoltaic (PV) panels dual axis solar tracking system. Unlike fixed or single axis tracking systems, dual axis trackers enable solar panels to track the sun’s movement on horizontal (azimuth) and vertical (elevation) axis. The capability to adjust solar panels in elevation and azimuth throughout the entire day permits the structures to maintain perpendicular alignment to the incoming sunlight, thus improving solar irradiance and power generation. The project consists of developing a working prototype which incorporates an Arduino based control system with LDRs for detecting sunlight position, steering mechanical movements via geared DC motors coordinated with dual H-bridge motor drivers for rotational control. Geared DC motors are used for mechanical movements while the direction control is performed by dual H-bridge motor drivers. The real-time adjustments are performed by LDRs positioned at strategic locations measuring varying levels of sunlight. Aspects of the designed dual axis system with regard to energy efficiency were analyzed and the outcomes were benchmarked against fixed and single axis models under diverse weather conditions and physical locations. Some of the most important measures of evaluation were energy productivity per day, precision of tracking and responsiveness of the system. Experimental data showed that dual-axis tracking systems had higher energy output as compared to fixed panel systems by 27.49% in energy efficiency, demonstrating the effectiveness of real time solar energy collection adjustments. Continuous, real-time manipulation provides maximized harvesting potential, especially during low-light sunlight angle times in early mornings and late afternoons. This study illustrates the strength dual-axis tracking systems have in making PV systems more effective and practical, especially for areas with high variability in solar energy. Moreover, the usage of inexpensive materials such as Arduino microcontrollers and LDRs makes the implementation of this technology affordable for small-scale and residential purposes. Further plans include developing the prototype for long-term testing along with adding weather forecast algorithms for predictive tracking and employing machine learning for enhanced tracking precision and energy efficiency