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In this paper, a new maximum power point tracking (MPPT) framework for photovoltaic (PV) systems is presented based on the remora optimization algorithm (ROA) subjected to standard and partial shading conditions. The studied system includes a PV array, a DC/DC converter, and a load and MPPT control system. The control variable is the voltage, and the optimization variable is the converter duty cycle, which is optimally determined using the ROA that is inspired based on the parasitic behavior of remora for achieving the maximum power of the PV system. In this study, the ability of the ROA is compared with manta ray foraging optimization (MRFO) and particle swarm optimization (PSO) methods for the MPPT solving of different shading patterns in view of extracted power, efficiency, and tracking rate. The results show that the ROA is a competitive method with higher efficiency in maximum power tracking and convergence accuracy than the MRFO and PSO for the MPPT solving of different patterns with higher exploration power. Moreover, an examination of the two partial shading patterns also showed that the power extracted using the ROA is higher than the MRFO and PSO while also reaching the global power value more quickly. The ROA achieved a tracking efficiency of 99.97% in a partial shading condition, with faster tracking in comparison with the MRFO and PSO methods. Therefore, the ROA is a high-speed tracking optimization method for enhancing the PV system’s efficiency in standard and especially in shading conditions.

A New Maximum Power Point Tracking Framework for Photovoltaic Energy Systems Based on Remora Optimization Algorithm in Partial Shading Conditions