LFC of smart, interconnected power system in the presence of renewable energy sources using coordinated control design of hybrid electric vehicles

In recent years, the widespread adoption of renewable energy sources for electricity generation has been driven by their minimal environmental impact and easy accessibility. However, without adequate load frequency control to balance production and demand, the variability in wind energy production can cause significant frequency fluctuations. Additionally, the anticipated increase in the use of plug-in hybrid electric vehicles (PHEVs) on the demand side, with their substantial battery storage and bidirectional charge/discharge capabilities, presents an opportunity to mitigate these fluctuations. Therefore, it is essential to design controllers that account for the uncertainties in renewable energy parameters, such as variable wind power and load. This study employs the Ant Lion Optimization (ALO) algorithm to optimally set the parameters for Model Predictive Control (MPC) and Proportional-Integral (PI) controllers in the load frequency control section. The goal is to efficiently regulate the charging rate of PHEV batteries while utilizing renewable energy sources. The proposed method was tested by optimizing the battery charge of four different PHEV models—V1G, V2G, smart charge, and smart discharge—based on load frequency control using MPC design in a smart, interconnected, two-area power system. The results indicate that the MPC controller outperforms the PI controller in reducing network frequency fluctuations and enhancing power control in a smart, interconnected, two-area power system.