Deployment of the hydrogen supply infrastructure is one of most critical issues that must be addressed for a successful market transition to fuel cell electric vehicles (FCEV). Not only must hydrogen refuelling infrastructure be constructed, it must also be commercially viable and sell hydrogen to customers at retail prices that will encourage the continued expansion of the vehicle market. The objective of this study is to develop a station deployment optimization model and analyze station network economics and risk of investment. The model optimizes key deployment decisions to meet fuel demand by trading off infrastructure cost and fuel accessibility cost. Decision variables are when, where to build and the size of stations. Fuel accessibility cost is relative to gasoline, measured by additional detour time in order to access hydrogen refuelling stations. A case study is conducted for the City of Santa Monica in California. Deployment schemes generated from the optimization model are relatively robust to assumed level of fuel inconvenience cost, suggesting that the importance of station scale economy outweighs fuel convenience, subject to the caveats of model limitations. The model does not capture the dynamic interaction between vehicle demand and refuelling convenience. If vehicle demand was modelled endogenously, the importance of refuelling convenience would be valued higher by the model. Another factor might be that the area of study is small, which limits potential detour time savings that could be achieved from adding more stations. Cash flow analysis results suggest that the station network at the study area (the city of Santa Monica) may endure negative cash flows for about a decade. Driving patterns of early FCEV adopters matter to the economics of city station network. If FCEV users on average have long annual driving distance and trips are concentrated within the region, the profitability of local station networks would be improved.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited