Integrated RES With Intelligent MPPT For Efficient Power Generation & Wireless Transmission for PV Applications

Abstract

The increasing global energy demand and the urgent need to shift to sustainable practices have made the integration of renewable energy sources (RESs) into distribution power systems imperative. This project's main objective is to implement rooftop photovoltaic (PV) systems as an essential part of low-voltage (LV) DC networks' building-integrated centralized generation Maximum Power Point Tracking (MPPT) using Artificial Neural Networks (ANNs) is used to maximize power extraction from photovoltaic (PV) panels and boost power generation efficiency, particularly in partially shaded circumstances. After that, the PV system's generated power is sent to a Luo converter, which effectively tracks and optimizes the power production. For wireless power transmission, the Luo converter's output is then fed into a high-frequency converter. This wireless power transmission improves the system's adaptability and scalability by facilitating smooth energy transfer without the requirement for physical connections. An isolation transformer is attached to the high-frequency converter's output in order to guarantee the system's dependability and safety. The high-frequency converter is isolated from the downstream components by the isolation transformer, which also offers protection against electrical risks. Finally, a battery made especially for use in electric vehicle (EV) applications receives the transformer's isolated output, which is also supplied to DC loads. Finally, we will use the MATLAB 2021a / Simulink program to do a number of numerical simulations in order to validate the suggested controls. The output voltage of 130v is stored in the battery if a voltage of 65 v is taken as output from the photovoltaic system.