Utilizing Genetic Algorithm Based FOPID Algorithm for Improving Grid Voltage Stability during EV Integration with High Renewable Penetration

Abstract

The integration of Electric Vehicles (EVs) into contemporary power grids leads to several problems, including elevated fault currents, frequency deviations, and voltage instability. The increasing number of electric vehicles creates greater risks for power grid stability and reliability, particularly when renewable energy sources dominate the power grid and temporary power interruptions occur. The research presented here analyzes different control systems to mitigate risks while studying how high EV penetration affects power grid stability.

The paper presets a Fractional Order Proportional-Integral-Derivative (FOPID) controller optimized. Two approaches, involving Particle Swarm Optimization and (PSO) Genetic Algorithms (GA) are employed for addressing instability problems in power grids with high renewable energy penetration. The results from the simulation demonstrate that the FOPID controller optimized using both PSO and GA provides exceptional improvements for Low-Voltage Ride-Through (LVRT) performance and voltage stability, providing significantly better performance with the increased EV penetration. However, for most parameters, the GA based system has a marginally better performance. The research demonstrates that EV charging stations can be successfully and stably integrated to the grid using appropriate control systems even with high renewable penetration.