Revolutionizing Photovoltaic Systems: An Innovative Approach to Maximum Power Point Tracking Using Enhanced Dandelion Optimizer in Partial Shading Conditions

Partial shading (PS) is a prevalent phenomenon that often affects photovoltaic (PV) installations, leads to the appearance of numerous peaks in power-voltage characteristics PV cells, caused by uneven distribution solar irradiance on module surface, known as global and local maximum power point (GMPP LMPP). In this paper, new technique for achieving GMPP based dandelion optimizer (DO) algorithm proposed, inspired movement seeds wind. The proposed aimed enhance efficiency generation systems, particularly under PS conditions. However, DO-based MPPT compared with other advanced tracker (MPPT) algorithms, such Particle Swarm Optimization (PSO), Grey Wolf (GWO), Artificial Bee Colony (ABC), Cuckoo Search Algorithm (CSA), Bat (BA). Simulation results establish superiority effectiveness used terms tracking efficiency, speed, robustness, simplicity implementation. Additionally, these reveal DO exhibits higher performance, root mean square error (RMSE) 1.09 watts, convergence time 2.3 milliseconds, absolute (MAE) 0.13 watts.