Enhancing Grid Stability-Bi-Directional V2G Integration in IEEE Distribution Networks with PSO

This paper investigates the integration of bidirectional Vehicle-to-Grid (V2G) technology into the IEEE 33- bus distribution network to enhance grid stability, voltage regulation, and peak load management. V2G technology enables electric vehicles (EVs) to act as distributed energy resources, contributing to reactive power compensation and supporting voltage levels within the acceptable range of 0.95–1.05 p.u. Using a Particle Swarm Optimization (PSO) algorithm, the study identifies the optimal placement and sizing of EV batteries based on a 24-hour load forecast, emphasizing high-demand scenarios. The methodology incorporates load flow analysis, system constraints, and the dynamic interplay of EV charging and discharging cycles. The results demonstrate that strategically placed V2G-enabled EVs can significantly reduce peak demand by discharging energy during high-load periods, thereby decreasing the reliance on additional generation capacity. Additionally, EV integration enhances voltage stability and minimizes infrastructure stress, contributing to more resilient grid operations. However, the PSO algorithm exhibited certain limitations, including sensitivity to parameter settings and a tendency toward premature convergence, which may impact the optimization’s accuracy. These findings highlight the potential for hybrid optimization approaches to address such limitations and refine system performance. This research presents a scalable and practical framework for integrating V2G technology into modern power systems, aligning with the growing demand for renewable energy and sustainable energy management. By addressing critical challenges in EV deployment and grid stability, this study provides actionable insights for grid operators and paves the way for future advancements in optimization techniques and real-time control strategies for high-EV-penetration networks.