Intelligent Vehicle-to-Grid Integration for Smart Grid Resilience and Dynamic Power Management: Modeling and Performance Evaluation Using MATLAB/Simulink

Abstract

In this study, an intelligent V2G-enabled smart grid framework for dynamic power management and evaluation of grid resilience via MATLAB/Simulink is proposed. The energy storage system of an EV is modeled with Battery (Table-Based) model, a variable resistor dynamic load, current and voltage monitor, and an SOC monitoring subsystem. All these elements are incorporated into the developed model along with the utility grid which is modeled as a DC voltage source. The load resistance is varied using a Step-controlled Variable Resistor, and the load resistance changes from 5 Ω to 2 Ω at 5 seconds, to simulate the conditions during peak demand. The proposed framework was tested for various simulation scenarios to examine the voltage stability, current response, battery performance, and the adaptability of the system under different loads. The simulation results showed a maximum voltage regulation of approximately 400 V during the entire operating period. The simulation results confirmed the grid voltage to be stable at about 400 V for the entire operating time, thus, showing the capability of a good voltage regulation. The load current was increased to 200 A during maximum load condition, while under normal load condition was around 80 A, showing the effectiveness of the dynamic load modeling approach. Moreover, the SOC monitoring has been able to successfully monitor the battery behaviour and energy utilization during system operation. The developed MATLAB/Simulink model offers a practical platform to analyze the interaction between EVs and the grid, dynamic power management strategies, and the operation of the smart grid for various operating conditions in a resilient manner.