A Real Time Implementation of ANN Controller to Track Maximum Power Point in Solar Photovoltaic System

Abstract

The primary objective of this work is to develop a cost-effective photovoltaic monitoring system capable of detecting the solar panel's maximum power point and transferring it to the load through the converter. This will be accomplished by using a DC-DC boost converter with an soft computing approach to monitor the maximum power and transmit everything to the load through the converter. Three essential elements of the anticipated system are a PV panel, a smart controller, and a DC-DC converter. The entire systems primary component is the smart controller, which uses Artificial intelligence to monitor the maximum power output from the photovoltaic panel and produce a reference voltage for controlling the converter. A complete and accurate simulation is performed with the suggested algorithm, the prescribed methods are designed and tested, and experiments on the prototype is conducted. The proposed controller exhibits different variables of solar photovoltaic systems via an LCD display. The scheme uses a number of sensing devices in the solar photovoltaic conversion process to retrieve and show different solar photovoltaic characteristics. Finally, to commercialize the designed framework as a product proficient of monitoring, displaying, and boosting power in remote or rural areas in accordance with the development of solar PV supply. A thorough simulation with an intelligent controller is designed and tested, as is experimental research on the prototype lines..