Risk-aware two-stage stochastic short-term planning of a hybrid multi-microgrid integrated with an all-in-one vehicle station and end-user cooperation

Abstract

The interconnection between different energy networks considerably improves their technical and economical aspects; however, it increases the complexity of decisions. This paper optimizes the short-term planning of a hybrid multi-microgrid integrated with an all-in-one vehicle station composed of charging facilities, battery swapping slots, parking lots and hydrogen and gasoline refueling parts. In order to achieve the optimal operation in such a complex system and consider the influence of day-ahead and real-time decisions under uncertainties, a risk-aware two-stage stochastic programming is suggested in the presented study. In this regard, fluctuations of wind and solar units and different types of electrical and thermal loads and markets are modeled using various scenarios and their risk is measured by the downside risk method. In addition, the impact of end-user cooperation is analyzed and a sensitivity analysis is implemented. The simulations demonstrate that the proposed model can successfully specify the behavior of all components under a risk-averse strategy with maximum robustness, where the profit is decreased by 8.4 % to achieve an expected risk in profit equal to 0 $. The results also validate that although the all-in-one station can act as a bulk storage, a multi-directional energy injection is required to provide its high demand.