Development of Intelligent Adaptive Control for Solar-SEIG Powered Battery Charging Station

Abstract

This paper presents the design and hardware-in-the-loop (HIL) implementation of a smart adaptive control strategy for a renewable-integrated electric vehicle (EV) charging station. The primary objective of this work is to develop a reliable, grid-compliant, and power-quality-enhanced charging station capable of operating under dynamic and critical load conditions. The proposed system integrates a solar photovoltaic (PV) array, a self-excited induction generator (SEIG) driven by a hydro turbine, battery storage, multiple EV charging ports, a critical load, and a three-phase utility grid. An adaptive least mean absolute third (ALMAT) filter-based control algorithm is employed to generate reference source currents, enabling effective harmonic mitigation, load balancing, and power factor correction. The system operates in both standalone and grid-connected modes, ensuring uninterrupted power supply during night time and optimal energy utilization during day time through battery storage and grid export. A bidirectional converter is used to support different types of EV charging requirements. Experimental validation using OPAL-RT demonstrates that the proposed control strategy achieves unity power factor, maintains total harmonic distortion within IEEE 519 limits, and ensures stable system performance under varying operating conditions. The results confirm that the developed charging station enhances power quality, improves system reliability, and supports sustainable and economical EV charging, making it suitable for practical deployment in renewable energy-based transportation charging station.