• Vijay Chavda

Photovoltaic (PV) systems'' efficiency is significantly impacted by how the solar panels are oriented in relation to the sun's position. Because the sun's path changes during the day, even simple and low-cost fixed-angle photovoltaic panels often fail to capture the full quantity of solar radiation. This work explores the use of two bio-inspired metaheuristic algorithms, Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO), to improve the tilt and azimuth angles of PV panels for improved solar tracking performance. Using simulated data matching to Maharashtra, India, the algorithms maximize net energy output by optimizing panel angles throughout the day, accounting for both harvested energy and tracking energy usage. According to the results, the WOA-based tracking system generates 1484.25 Wh of energy per day, which is 15% more than the fixed system. The generation of the PSO-based system is 1397.00Wh, which is 8.68% more than that of the fixed-angle system, which is 1285.41 Wh. The study found that intelligent solar tracking significantly boosts PV efficiency and that, in this particular scenario, WOA is a better optimization technique than PSO.

Particle Swarm Optimization, Solar Tracking, Whale Optimization Algorithm

"WOA-Based Evaluation of Solar Tracking's Impact on Photovoltaic Efficiency", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 9, page no.127-129, September-2020, Available :http://www.jetir.org/papers/JETIR2009481.pdf

"WOA-Based Evaluation of Solar Tracking's Impact on Photovoltaic Efficiency", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 9, page no. pp127-129, September-2020, Available at : http://www.jetir.org/papers/JETIR2009481.pdf