Novel energy management and harnessing wind power for sustainable electric mobility of multi-micro grid system

Recent developments, marked by a surge in renewable energy adoption and a substantial integration of Plug-in Electric Vehicles (PEVs) into microgrid systems, present significant challenges for effective energy management in these systems. However, existing energy management methods are hindered by limited robustness against uncertainties in renewable energy generation. To address this, a robust stochastic optimization model has been developed in this study. The model empowers control entities to manage generation and storage assets by regulating PEV charging behavior, aiming to minimize overall costs. A novel bi-level strategy is introduced to reduce reliability costs, employing a vehicle-to-grid (V2G) tool to optimize the system's cost. The energy management model for the microgrid (MG) in the grid-connected mode considers uncertainties in the output power of wind turbines (WT), as well as the charging and discharging activities of PEVs. This work addresses the above-mentioned issues in a Multi-Micro Grid (MMG) system, for making it close to real time practical applications. The results indicate that the incorporating this bi-level strategy allows the MMG system to operate with the minimal cost and optimum reliability.