Integrated design for rural microgrids in Egypt incorporating hydrogen energy and vehicle-to-grid technology

Green hydrogen (H₂) has gained considerable attention as a cornerstone of a zero-emission future. The global transportation sector is shifting from gasoline-powered vehicles toward electric vehicles (EVs) and hydrogen vehicles (HVs) to reduce emissions. This paper investigates a microgrid (MG) model comprising photovoltaic panels, wind turbines, batteries, and hydrogen energy storage systems integrated with vehicle-to-grid (V2G) systems for EVs and HVs. The stochastic behavior of both EVs and HVs is characterized using probability density functions to capture vehicle uncertainty. A double-layer optimization model is proposed to enhance the reliability, cost-effectiveness, and sustainability of MGs. The upper layer employs the non-dominated sorting genetic algorithm II to optimize V2G scheduling, thereby minimizing MG load variance and total operational costs for EV and HV owners. The lower-layer approach is a multi-objective optimization problem that minimizes system costs over the entire life cycle while maximizing MG reliability, solved using the Gurobi optimizer. The framework is validated for an islanded MG in El-Kharga Oasis, Egypt, as an off-grid community with high renewable energy potential. Various scenarios are examined for EV and HV behavior, with the optimal cost achieved when G2V and V2G modes are applied to both HVs and EVs, resulting in a 12% cost reduction relative to the scenario without V2G. Further analysis is conducted to examine the impact of the loss-of-power-supply probability (LPSP) value on system economics. Results indicate that implementing an LPSP constraint of 0.05 reduces the annualized total cost by around 21.2% compared to the baseline case without the LPSP constraint.