@article{article_1813934, title={INFO algorithm based MPPT optimization of a photovoltaic system under partial shading conditions}, journal={Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi}, volume={32}, year={2025}, DOI={10.65206/pajes.79484}, author={Koç Savaş, Kezban and Demirtaş, Mehmet and Çetinbaş, İpek}, keywords={Friedman Testi, INFO, Maksimum Güç Noktası, MPPT, Kısmi Gölgeleme, Fotovoltaik}, abstract={Obtaining maximum efficiency from photovoltaic (PV) systems through maximum power point tracking (MPPT) remains an ongoing challenge. In this study, the weighted mean of vector (INFO) algorithm is employed to address and solve the MPPT problem for a photovoltaic system operating under partial shading. Besides INFO algorithm, electric eel optimization (EEFO), red-tailed hawk algorithm (RTHA), and student psychology-based optimization (SPBO) algorithms were also employed, and this study is the first to employ these optimization algorithms for MPPT purposes. The particle swarm optimization (PSO) algorithm, which is frequently employed in MPPT studies, is employed to compare the performance of new metaheuristic algorithms. These algorithms are tested with challenging shading scenarios where the local maximum points (LMPPs) and global maximum power point (GMPP) varied. The performance of these algorithms is evaluated using the Friedman test, which is a statistical test, and performance metrics. According to the findings of the comparison, the INFO algorithm is the most effective among the five algorithms for MPPT optimization under partial shading conditions, and this conclusion is confirmed statistically. Additionally, experimental tests were conducted to evaluate the performance of the INFO algorithm on real hardware. A programmable PV simulator, boost converter, and STM32 board were used. The experiments demonstrated that the algorithm could quickly and stably track the maximum power point.}, number={3}, publisher={Pamukkale Üniversitesi}