Stochastic optimal design of a rural microgrid with hybrid storage system including hydrogen and electric cars using vehicle-to-grid technology

In this paper, the optimal sizing of a rural microgrid is studied by applying two-stage stochastic programming with a scenario-based approach considering a multi-energy system and different electric vehicle technologies with grid-vehicle-grid operations. The system components are a photovoltaic panel, wind turbine, battery, hydrogen-based storage, battery electric vehicle (BEV), and fuel cell electric vehicle (FCEV). A multi-objective optimization problem with minimizing life cycle cost and maximizing the system reliability is defined for the microgrid design. To reflect reliability, loss of power supply probability (LPSP) indice is used. The defined problem is solved with mixed-integer linear programming. Hourly real-world data for a one-year period is used for simulations. The uncertainties from renewable resources, demand, BEV, and FCEV users are considered during system design. Firstly, we analysed the impact of different storage technologies on system design. We found that a hybrid storage system is the most cost-effective option for each LPSP limit and increasing LPSP from 0 to 0.2 led to a cost reduction of up to 20% in all cases. Secondly, different cases are created to assess the impact of BEVs and FCEVs in capacity configuration considering grid-vehicle-grid operations. Simulation results demonstrate that utilizing vehicle-to-grid (V2G) mode in both types of vehicles leads to a cost reduction of approximately 2% when a hybrid storage system is in place. Furthermore, it is observed that BEVs contribute significantly, providing up to 90% of the V2G power. Also, the availability of FCEV with a larger size of fuel tank capacity affects positively the cost of the designed system.

Automated summary

This paper studies the optimal sizing of a rural microgrid by considering a multi-energy system and different electric vehicle technologies with grid-vehicle-grid operations. A two-stage stochastic programming approach is applied using a scenario-based method. The study defines a multi-objective optimization problem to minimize life cycle cost and maximize system reliability, using the loss of power supply probability indice. The results show that a hybrid storage system is the most cost-effective option and utilizing vehicle-to-grid (V2G) mode can lead to cost reduction.