Designing Optimal LNG Station Network for U.S. Heavy-Duty Freight Trucks using Temporally and Spatially Explicit Supply Chain Optimization

The recent natural gas boom has opened much discussion about the potential of natural gas and specifically Liquefied Natural Gas (LNG) in the United States transportation sector. The switch from diesel to natural gas vehicles would reduce foreign dependence on oil, spur domestic economic growth, and potentially reduce greenhouse gas emissions. LNG provides the most potential for the medium to heavy-duty vehicle market partially due to unstable oil prices and stagnant natural gas prices. As long as the abundance of unconventional gas in the United States remains cheap, fuel switching to natural gas could provide significant cost savings for long haul freight industry. Amid a growing LNG station network and ever increasing demand for freight movement, LNG heavy-duty truck sales are less than anticipated and the industry as a whole is less economic than expected. In spite of much existing and mature natural gas infrastructure, the supply chain for LNG is different and requires explicit and careful planning.;This thesis proposes research to explore the claim that the largest obstacle to widespread LNG market penetration is sub-optimal infrastructure planning. No other study we are aware of has explicitly explored the LNG transportation fuel supply chain for heavy-duty freight trucks. This thesis presents a novel methodology that links a network infrastructure optimization model (represents supply side) with a vehicle stock and economic payback model (represents demand side). The model characterizes both a temporal and spatial optimization model of future LNG transportation fuel supply chains in the United States. The principal research goal is to assess the economic feasibility of the current LNG transportation fuel industry and to determine an optimal pathway to achieve ubiquitous commercialization of LNG vehicles in the heavy-duty transport sector. The results indicate that LNG is not economic as a heavy-duty truck fuel until 2030 under current market conditions unless a significant station capital subsidy, upwards of 50 percent and even then it might not be enough. However, a doubling of LNG truck demand will initialize network commercialization in the modeling base year, 2012 (the same year Clean Energy Corp. launched their national LNG network) in California and then gradually establish in other hotspot regions in Mid-West and Mid-Atlantic throughout the time horizon. The model shows that trucking routes in California are highly commercial due to high traffic volume and regional advantages. The model can be used by industry to inform necessary policies and to plan future infrastructure deployment along trucking routes that are likely to provide the highest returns.