Improved Rat Swarm Optimizer Algorithm-Based MPPT Under Partially Shaded Conditions and Load Variation for PV Systems

Photovoltaics are exposed to partial shading conditions (PSCs). Bypass diodes are installed across series-connected PV modules to avoid the hotspot phenomena, which causes several peaks on the power curve. While a new approach has been presented to distinguish between the uniform shading conditions (USC_S) and the PSC_S to reduce unnecessary search space area, it leads to faster convergence speed (CS). This paper proposes an improved Rat Swarm Optimizer algorithm (IRSO), based on maximum power point tracking (MPPT), to increase the convergence speed towards the maximum power point. Furthermore, a new approach has been developed to improve speed response during load variation for any dc-dc converter. To make the algorithm more straightforward, one dynamic tuning parameter is used. The proposed method was tested experimentally by implementing a SEPIC converter and the sampling time was adjusted at 0.05 s. The proposed method was successfully implemented experimentally, with an average tracking time of less than 1 s and an efficiency of 99.89% for different irradiance values and load varying conditions. Moreover, the comparison between the proposed method and the metaheuristic algorithms in this domain is implemented and shows the effectiveness of the proposed method in terms of fast tracking, simple implementation and high efficiency.