Resilient Operation of PV Systems in Weak Grids by adjusting of Flexible Grid Conditions through Artificial Neural Networks (ANNs) to Improve Power Quality

Abstract

The solar Photovoltaic Array (PVA) producing unit reported in this study is conducted to an inadequate utility grid for distribution. A boost converter using the incremental conductance (InC) approach optimizes PVA power. The weak grid can be affected by distortions, imbalances, voltage sags, and voltage swells. Grid Voltage Filtering (GVF) is a stage in the control system that prevents errors in the grid voltage that might affect the controlled grid current. Furthermore, any DC offset in the voltage signal is neutralized by the GVF. When operating under poor grid conditions, the DC link voltage is flexible-regulated to prevent excessive modulation. Grid power quality is maintained by flexible regulation, even in severe instances of voltage imbalance. Variations in PVA power, load currents, and grid voltages can all be tolerated by the system. Accurate measurement of load current weights can help avoid DC link voltage discrepancies during load swings.