Electric vehicles (EVs) improve the performance of Energy Storage Systems (ESS). The inclusion of electric vehicles in the microgrid system has attracted considerable attention due to the emerging potential of vehicle-to-grid options. The proper coordination among ESS & EVs has a high capacity to tolerate frequency discrepancies and the functioning of the MG (Micro-Grid). In this research, two innovative control techniques-To address the issue of frequency regulation in the standalone MG, Model Predictive Control (MPC) and Dynamical Droop Control (D2C) are linked to affect the structure of ESS and EVs following extensive RES inclusion or a significant change in load demand. The D2C protects EV energy in line with system demands by preserving the least amount of power for anticipated EV demand. Combined MPC and D2C settings are tuned using a complex evolutionary technique to further improve performance. In MATLAB/Simulink, a single MG (micro-Grid) is modeled and evaluated using the controlling strategies indicated above. As well, a range of case papers is taken into account to confirm the integration of the D2C and MPC for a single MG's modulation scheme. Moreover, the MPC outperforms both fuzzy-based proportional-integral (FPI) and proportional-integral (PI) controllers in terms of performance results.