Detailed Spatial Modeling of Coal-based Hydrogen Infrastructure Deployment with Carbon Capture and Storage: Methods, Implications, and Insights.

摘要

The use of hydrogen as a transportation fuel has been proposed as a potential solution to three major issues facing the transport sector: climate change, energy security, and local air quality. However there are significant barriers to the introduction of hydrogen, including the cost and performance of vehicle technologies (e.g., fuel cells and onboard storage) and the cost and lack of a hydrogen infrastructure (e.g., production and storage facilities, distribution networks, and refueling stations). The development of this infrastructure is considered a major obstacle since it will require significant capital investment over a long time period with high investment risk. Consequently, models are needed that can identify the magnitude of required infrastructure and evaluate its cost for various deployment strategies. Most existing hydrogen infrastructure models are steady-state models that estimate infrastructure design and cost at a fixed point in time. These models assume that the infrastructure is perfectly sized for the current hydrogen demand and, thus, estimate the levelized cost of hydrogen assuming fully utilized infrastructure. Yet, the reality is that much of this infrastructure (e.g., centralized production facilities) will need to be installed in relatively large sizes, rendering it difficult to perfectly match supply and demand throughout a transition. As a result, it is likely that infrastructure capacity will be underutilized to varying degrees during deployment. Another weakness of existing models is that they rarely incorporate the spatial aspect of infrastructure design and, when they do, simplified spatial representations are used. However, the optimal design of hydrogen infrastructure will likely depend on regional characteristics, such as feedstock prices, the spatial distribution of hydrogen demand, and the locations of potential sites for hydrogen production and transport. Consequently, detailed spatial data will likely yield important insights into the design and cost of hydrogen infrastructure.;This dissertation presents a new model that better accounts for the spatial and temporal aspects of infrastructure deployment. In Chapter 2, a novel modeling method is described that combines detailed spatial data with optimization tools to evaluate how hydrogen infrastructure might develop in specific geographic regions over time. Unlike existing infrastructure models, the model described in this document utilizes higher resolution spatial data and has the capability to identify integrated regional pipeline networks that connect multiple production facilities to multiple demand centers (i.e., cities). In addition, by tracking infrastructure investments over time, the model accounts for underutilization of infrastructure given different scenarios for hydrogen fuel cell vehicle (HFCV) deployment. Although the model can be applied to multiple infrastructure pathways, this research focuses on centralized coal-based hydrogen production with carbon capture and storage (CCS) and distribution of hydrogen by pipeline. In Chapter 3, the model is applied to a case study in the western United States, which explores optimal strategies for deploying hydrogen infrastructure in a large region. This chapter discusses the design, cost, greenhouse gas emissions, and CO2 capacity constraints under different deployment strategies and subsidy scenarios. In Chapter 4, the model is applied to several sub-regions in the western United States in order to better understand how regional characteristics impact the design and cost of hydrogen infrastructure.