Smart Grid Integration of Electric Vehicle and PV Systems with Ant Colony and Neural Network Based Control System

The transition to Renewable Energy Sources (RES) grows more depend on Electric Vehicles (EVs) and distributed RES, particularly Photovoltaic (PV) systems, to decrease greenhouse gas emissions and improve energy storage capacity. Effective energy management strategies are required to fully exploit the potential of EVs while maintaining continuous grid operation. To increase Power Quality (PQ) and optimize grid integration, this work proposes an intelligent PV-EV integrated high-gain extended DC-DC converter, and an Artificial Neural Network (ANN)-based controller. The high-gain extended converter utilized for improving voltage and energy transfer between the PV system and the grid. The Ant Colony Optimized-Proportional Integral (ACO-PI) controller employed for optimizing DC-bus voltage regulation under dynamic operating conditions, whereas the ANN controller ensures accurate grid current tracking and efficient power supply. In this work implemented by MATLAB simulation, thus the converter attains 93.7 % and the THD values attains 0.08 % (R phase), 0.06 % (Y phase), 0.05 % (B phase). The integrated operation of these controllers improves system stability, dynamic response, and grid performance, allowing for the reliable integration of PV systems and EV batteries into modern smart grids.