Smart EV Charging Infrastructure Using IOT and AI for Intelligent Energy Management and Grid Optimization

Abstract

The rapid adoption of electric vehicles (EVs) has created an urgent need for intelligent charging infrastructure capable of supporting increasing energy demand while maintaining grid stability and charging efficiency. Conventional EV charging stations often suffer from challenges such as unbalanced power distribution, long charging durations, inefficient energy management, and limited integration with renewable energy resources. This paper proposes a Smart EV Charging Infrastructure that integrates Internet of Things (IoT)-enabled sensing, cloud-based monitoring, renewable energy sources, battery energy storage, and artificial intelligence (AI)-based energy management to provide an efficient, reliable, and sustainable charging solution. The proposed framework continuously monitors charging parameters, battery state-of-charge, grid conditions, and renewable energy availability to optimize charging schedules using intelligent decision-making algorithms. A cloud platform enables real-time monitoring, remote control, predictive maintenance, and data analytics, while dynamic load balancing minimizes peak demand and improves power quality. Renewable energy integration reduces dependence on the utility grid and lowers carbon emissions, whereas battery storage enhances charging reliability during peak demand periods. The proposed system also supports secure communication between charging stations, EVs, and utility operators to facilitate smart grid interaction. Experimental evaluation demonstrates improvements in charging efficiency, energy utilization, grid load balancing, and operational reliability compared with conventional charging approaches. The proposed infrastructure provides a scalable, energy-efficient, and environmentally sustainable solution for future smart transportation ecosystems and intelligent energy management.