Abstract
Controlling the single-phase PV system improves system performance, safety, reliability, and controllability while interacting with the energy grid. The primary goal of this research is to create an Artificial Neural Network (ANN) vector control method for a single-phase solar inverter. The ANN controller is trained using approximation dynamic programming to obtain optimum control. To evaluate an ANN-based solar PV system, models of PV system behaviour for grid integration and maximum power extraction from solar PV arrays in a genuine residential PV application, as well as the development of an experimental solar PV system, are employed. The findings show that an ANN-controlled PV system outperforms a typical vector-controlled PV system in terms of performance.
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