单相两阶段并网光伏系统采用OSO-AI控制与PSPO最大功率点跟踪

This paper introduces an Optimized Second-Order Adaptive Integrator (OSO-AI) control and ground-breaking Predictive Self-Tuned Perturb & Observe (PSPO) Maximum Power Point Tracking (MPPT) technique for a single-phase two-stage grid integrated Solar Photovoltaic (SPV) system, aimed at enhancing power quality in distribution networks. The architectural structure includes a boost converter and a Voltage Source Converter (VSC), designed to maximize solar power extraction and ensure seamless grid integration with minimal harmonics. The system’s Point of Common Coupling (PCC) have two distinct non-liner loads. The proposed OSO-AI control algorithm effectively manages the VSC to provide reactive power compensation and improve grid stability. Extensive simulation tests and rigorous laboratory experiments on hardware system are performed to verify its robustness against dynamic load perturbations, grid disturbances, and fluctuating solar irradiance. The experimental results demonstrate the robustness of the proposed approach, with total harmonic distortion (THD) under 5%. The findings highlight the system’s compliance with stringent power quality norms, validating the effectiveness of the PSPO MPPT and OSO-AI control in optimizing performance in grid-connected SPV systems.