Analysis of fault ride through the improvement of PV power plant based on artificial neural network

Abstract

The increasing adoption of renewable energy sources in industrial areas, driven by the need to both obtain a grid voltage from renewable energy sources and reduce high electricity bills, has led to an increased demand for solutions that can improve the power quality of these systems. A photovoltaic power plant (PVPP) based on a dc-chopper circuit protection system is proposed for the enhancement of the power quality of PVPP. The aim of the presented protection method is to protect the panels in the PVPP from the harmful effects of the high dc voltage that occurs during grid faults. The adaptive neural network control system is applied in both the T-type inverter and the dc-chopper circuit protection system. The proposed protection system is implemented with a 250 kW PVPP to verify its validity with simulation results during grid fault. This approach can potentially improve the reliability and stability of PVPP, and contribute to the maintain of PVPP into the grid.