• Volume: 2
• Issue:01
• Date: 01-01-2025

Title : Analyzing the Impact of Electric Vehicle Charging on Grid Congestion and Load Management: A Comprehensive Review

Abstract: The integration of electric vehicles (EVs) and renewable energy sources (RES) is transforming modern power systems, offering a pathway toward sustainable and low-carbon energy solutions. However, the increasing penetration of EVs and intermittent renewable generation poses significant challenges for grid stability, load balancing, and energy distribution. The uncoordinated charging of EVs can lead to grid congestion, peak load surges, and voltage fluctuations, while the variability of renewable energy sources such as solar and wind further complicates grid management. This review paper examines the role of smart energy integration in addressing these challenges by leveraging intelligent charging strategies, demand-side management, and advanced energy storage solutions. It explores various smart grid technologies, including Vehicle-to-Grid (V2G) systems, artificial intelligence (AI)-driven charging algorithms, blockchain-based energy trading, and real-time load forecasting models, that enable the seamless integration of EVs and renewable resources. Additionally, this study highlights the significance of policy frameworks, regulatory incentives, and infrastructure advancements in fostering a resilient and adaptive energy ecosystem. By analyzing recent research, case studies, and emerging smart grid innovations, this paper provides valuable insights into scalable and efficient energy management strategies that optimize EV charging while enhancing grid reliability and renewable energy utilization. The findings suggest that a holistic approach, combining technological advancements, regulatory support, and data-driven grid optimization, is crucial for achieving a sustainable and resilient power system.

Key Words: Electric Vehicle Charging, Smart Energy Integration, Renewable Energy, Grid Stability, Vehicleto-Grid (V2G), Demand Response, AI in Energy Management, Smart Grids, Load Balancing

Area: Engineering

• Approved ISSN: ----
• Paper Id: IJREISTU22
• Page No: 6-10

• Author: Rahul Kumar

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• Co- Author: Ashish Bhargava