Optimizing Bidirectional Power Flow in EV Charging Systems: Topologies and AI-Based Control for V2G/G2V and Renewable Energy Integration

As electric vehicles (EVs) become more popular and renewable energy sources like solar and wind are increasingly used, finding smarter ways to manage energy is essential. One promising solution is bidirectional EV charging systems, which allow energy to flow in two directions: from the grid to the vehicle (G2V) and from the vehicle back to the grid (V2G). These systems can support the power grid during high demand, store excess renewable energy, and help create a cleaner, more reliable energy system. This paper focuses on improving how these bidirectional charging systems work. It explores different hardware designs, called “topologies,” that make energy transfer more efficient and reliable. For example, advanced converters and inverters are discussed, which help reduce energy loss and ensure that the system can handle changes in energy demand and supply smoothly. The paper also looks at how EV charging systems can connect with renewable energy sources like solar panels or wind turbines to maximize their use and reduce reliance on traditional power plants. In addition to hardware, this research highlights the role of artificial intelligence (AI) in managing these systems. AI tools, like machine learning algorithms, are used to predict energy needs, optimize when and how energy flows, and prioritize using renewable power whenever possible. These intelligent systems can adapt in real time to changes in the grid, weather, or the needs of EV users, making the entire process smarter and more efficient. The paper also addresses real-world challenges, such as ensuring all EVs and charging systems can work together, keeping the grid stable during high energy usage, and making these systems affordable and practical for widespread use. Case studies and simulations show how these solutions can work in practice, highlighting benefits like lower energy costs, reduced carbon emissions, and a more resilient energy grid. Ultimately, this research demonstrates how combining advanced hardware and AI-driven controls can revolutionize EV charging systems. By better integrating renewable energy and enabling smarter energy management, these innovations support a more sustainable and efficient future for transportation and energy systems alike. The findings are valuable for anyone interested in cleaner energy, from researchers and policymakers to businesses and everyday EV users.