Improved MPPT technology for PV systems using Social Spider optimization (SSO): Efficient handling of partial shading and load variations

Photovoltaic (PV) systems are a key renewable energy source, but weather variability poses challenges in maximizing solar power capture, particularly under partial shading conditions (PSC), which cause local peaks and global peak. Various optimization strategies for tracking the global point have been proposed. While the complexity of the method, the number of tuning parameters, the convergence speed, and the fluctuations in load are the major drawbacks of these optimization techniques. This work proposes an enhanced Social Spider Optimization (ISSO) technique that improves the convergence speed towards the maximum power point. Furthermore, a novel method has been developed to improve speed response during load changes and can be implemented with all DC-DC converters. Different types of sophisticated partial shading conditions were tested using a SEPIC converter with a sample time of 0.05 s. According to the obtained results, the suggested ISSO approach has shown the excellent performance, with 0.63 s of average tracking time under various types of weather conditions and an efficiency of 99.97%. Moreover, a comparison is carried out to compare the proposed technique with current metaheuristic approaches. While the results demonstrates the effectiveness of the suggested algorithm regarding rapid tracking and improved efficiency.