Optimal design of microgrid-based resilient hybrid electric vehicle station by considering uncertainties

Designing a resilient hybrid electric vehicle station that integrates battery electric vehicle (BEV) charging and hydrogen refueling, supported by renewable energy sources and hybrid storage systems, is a forward-thinking approach to sustainable transportation infrastructure. This design not only improves energy security but also contributes to environmental sustainability. The system, in terms of local energy sources, consists of solar, wind, battery, and hydrogen storage systems. To design the system optimally, considering uncertainties arising from renewable generation variability, vehicle demand fluctuations, and electricity market prices, a two-stage stochastic programming model is utilized, integrating Conditional Value-at-Risk (CVaR) to explicitly address extreme tail risks linked to demand jumps and generation inconsistencies. We conduct a performance evaluation of the designed system under varying grid connection capacities, resilience constraints, and charger configurations. The analysis reveals significant trade-offs among system resilience, investment costs, and operational profitability.