UC Davis Institute of Transportation Studies

Southern California has been proposed as a likely site for developing a hydrogen refueling infrastructure. In this paper, we apply dynamic programming to identify optimized strategies for supplying hydrogen over time in Southern California. GIS-based traffic data are used to model the location and magnitude of hydrogen demand over time. Refueling stations are sited based on the location of demand and the trade-off between convenience and costs. We use engineering/economic models to describe a variety of possible hydrogen supply options. Both onsite and central production technologies including biomass gasification, coal gasification, natural gas reforming, and water electrolysis are investigated. For central production routes, several delivery modes are analyzed including liquid and compressed gas trucks, and gas pipelines. These technologies compete with each other to meet an exogenously estimated hydrogen demand over time at lowest cost. At each time step over a specified transition period, the model uses a dynamic programming algorithm to select the best strategy for building up the infrastructure. We find that 1) hydrogen could be cost competitive based on region-specific spatial optimization; 2) the best buildup strategy for Southern California could be industry hydrogen in early stage, bridged by onsite natural SMR and followed by biomass central gasification and then coal gasification with carbon capture and sequestration; 3) the feasibility of CCS is critical in CO2 emissions mitigation.