Locating hydrogen fuel stations: A comparative study for Istanbul

Abstract

World’s energy sources are depleting while the need for alternative energy resources is increasing. Hydrogen energy is an essential alternative and its use in transportation sector through Hydrogen Fuel Cell Vehicles (HFCV) is increasing day by day. For HFCV to become widely used, however, it is necessary to establish a good infrastructure, i.e., hydrogen should be accessible. In this study, we investigate the problem of locating Hydrogen Refueling Stations (HRS) in İstanbul, the most crowded city of Turkey. The problem is addressed with multi-period set covering model and the different population densities in the city are integrated with a modification of this model. Due to the long computational time required by the multi-period set-covering model, two heuristics, namely the iterative model and the reduced model, are proposed. The results indicate that for a geographically distinct city like İstanbul, using Euclidean distance may yield very drastic conclusions, hence should be avoided. It is also shown that the HRS are densely located in areas with high population, and one should trade-off between the total distance to be travelled by the drivers and being served by one of the closest stations. In a multi-period setting where stations are opened incrementally, the findings from two different heuristics favor different stakeholders: the iterative model offers advantages from the perspective of decision-makers, while the multi-period model with an optimality gap is advantageous from the perspective of customers. We also introduce the partial coverage model, which serves as a combination of set covering and p-median models, to analyze the transition if the demand is fulfilled incrementally, not completely. It turns out that less number of stations are sufficient to meet high demand, but the number increases significantly if all demand should be satisfied.