An Effective Salp Swarm Based MPPT for Photovoltaic Systems Under Dynamic and Partial Shading Conditions

This study proposes a duty cycle-based direct search method that capitalizes on bioinspired optimization algorithm known as the salp swarm (SSA). The goal is to improve tracking capability of maximum power point (MPP) controller for optimum extraction from photovoltaic system under dynamic environmental conditions. performance proposed SSA tested transition between uniform irradiances and partial shading (PS) conditions with focus convergence speed, fast accurate tracking, reduce high initial exploration oscillation, low steady-state oscillation at MPP. Simulation results demonstrate superiority in terms performance. better than conventional (hill-climbing) among other popular metaheuristic methods. Further validation conducted via experimental studies involving DC-DC buck-boost converter driven by TMS320F28335 DSP Texas Instruments Experimenter Kit platform. Hardware show aligns simulation fast-tracking, satisfactory accuracy PS tracks efficiency through its superficial structures concepts, well easy implementation. Moreover, maintains minimum level overall energy yield. It thus compensates shortcomings existing