Real-time validation of a Robust Intelligent control technique for Grid-Tied Photovoltaic Systems

The global demand for clean, renewable energy sources has significantly increased, particularly for photovoltaic (PV) systems, which require less maintenance and operational costs. They are known for their flexibility to support both off-grid and grid-connected applications, making them a key technology for modern sustainable energy systems. Grid-Tied PV Systems (GTPVSs) have attained attention due to their capability of injecting power directly into the electrical grid without the need for batteries, unlike the grid-off PV systems that require energy storage. The use of GTPVS minimizes battery maintenance and ensures the direct synchronization of the extracted PV power with the utility grid. Nevertheless, abrupt variations and partial shading in environmental conditions and grid disturbances may reduce the robustness and efficiency of these systems. For this purpose, improved and advanced control techniques are required for establishing high performance and superior power quality injection. The utility of these methods is crucial for establishing a fast tracking of the Maximum Power Point (MPP) and enabling a stable grid injection with international standard compatibility. Thus, a Robust Intelligent-Fuzzy Backstepping (RI-FB) control technique is introduced for improving the performance of GTPVS, by providing a fast tracking under Partial Shading Conditions (PSCs) and delivering a rapid power injection into the grid, even under grid disturbances, such as AC loads. The integration of robust backstepping and fuzzy logic ensures an optimal power tracking that exceeds 98 % in only 18 ms while maintaining the grid synchronization, and offering a minimized Total Harmonic Distortion (THD) below 0.90 %, surpassing other benchmarked strategies. The proposed RI-FB technique confirms its real-time feasibility through Processor-In-the-Loop (PIL) implementation using the TMS320F28335 platform, which presents a robust key for the GTPVS.