Exploring the Synergy of Flywheel Energy Storage and Genetic Algorithms in Hybrid Charging Infrastructure

Abstract

This paper studied about the synergy between flywheel energy storage systems (FESS) and genetic algorithms (GAs)-based optimization towards hybrid charging infrastructures that displays a great promise to revolutionize the energy management for efficient, sustainable, and reliable grids. FESSs are high-power-density storage devices with rapid response and durability. They complement GAs better with dynamic resource allocation towards optimized energy flow. The study dives into critical areas, such as the integration of renewable energy sources, bi-directional electric vehicle (EV) charging, and hybrid energy storage systems, showcasing their role in advancing modern energy systems. Comparative analysis highlights major gains, including improvement in fuel use by 28.5 percent, reduced reliance on traditional power grids, and enhancing the economic viability of hybrid energy systems. Despite these benefits, computational complexity and hardware-software integration remain among the challenges associated with this kind of framework. Robustness and adaptability in such a framework are called for. These findings underlie the transformative power of combining FESS and GA for the pressing challenge of energy solutions, especially for increasing global electrification and renewable energy integration. With actionable insights and innovative solutions, this review contributes to sustainable energy systems while supporting the demand for efficient and scalable electrification strategies.