[Paper Review] Nationally Scalable Hydrogen Fueling Infrastructure Deployment: A Megaregion Analysis and Optimization Approach

Vivek A. Sujan, Jinglian Fan+2 more|arXiv (Cornell University)|Oct 8, 2024

Integrated Energy Systems Optimization4 citations

TL;DR

This paper proposes a nationally scalable optimization framework, OR-AGENT, to design cost-effective hydrogen refueling infrastructure for medium- and heavy-duty vehicles (MHDVs) across key U.S. freight corridors, including the Texas Triangle and I-10/I-5 corridors. Using a genetic algorithm on integrated freight, energy, and mobility data, it identifies minimal, strategically located hydrogen stations that prevent vehicle stranding and support decarbonization goals for 8.5% of U.S. heavy-duty freight.

ABSTRACT

Decarbonizing regional and long-haul freight faces challenges due to the limitations of battery-electric vehicles and infrastructure. Hydrogen fuel cell medium- and heavy-duty vehicles (MHDVs) present a promising alternative, aligning with the Department of Energy's decarbonization goals. Historically, alternative fuels like compressed natural gas and propane gas have seen slow adoption due to infrastructure barriers. To prevent similar setbacks, planning for zero-emission hydrogen fueling infrastructure is critical. This research develops plans for affordable and accessible hydrogen refueling stations, supporting the decarbonized freight system and benefiting underserved and rural communities by improving air quality, reducing noise pollution, and enhancing energy resilience. It provides a blueprint for replacing diesel in Class 8 trucks with hydrogen fueling solutions, focusing on the Texas Triangle Megaregion (I-45, I-35, I-10), the I-10 corridor between San Antonio, TX, and Los Angeles, CA, and the I-5/CA-99 corridors between Los Angeles and San Francisco. This area accounts for ~8.5% of U.S. heavy-duty freight volume. Using the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transport) framework, the study analyzes vehicles, freight networks, and energy systems. The framework integrates data on freight mobility, traffic, weather, and energy pathways to deliver optimized powertrain architectures and hydrogen fueling infrastructure deployment. It assesses all vehicle origin-destination pairs and feasible fueling station locations, using a genetic algorithm to identify the minimum number and optimal locations of hydrogen stations. It also determines fuel schedules and quantities, ensuring no vehicle is stranded. A deployment roadmap outlines strategic hydrogen refueling infrastructure rollout across multiple adoption scenarios.

Motivation & Objective

• Address infrastructure barriers that previously hindered adoption of alternative fuels like CNG and propane.
• Enable decarbonization of regional and long-haul freight by replacing diesel-powered Class 8 trucks with hydrogen fuel cell vehicles.
• Ensure equitable access to hydrogen infrastructure for underserved and rural communities through strategic station placement.
• Develop a nationally scalable blueprint for hydrogen fueling infrastructure deployment across major freight megaregions.
• Minimize infrastructure costs while guaranteeing no vehicle is stranded due to insufficient refueling coverage.

Proposed method

• Utilizes the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transport) framework to model powertrain and infrastructure architectures.
• Integrates multi-source data on freight mobility, traffic patterns, weather, and energy pathways for realistic system modeling.
• Applies a genetic algorithm to optimize the minimum number and optimal geographic locations of hydrogen refueling stations.
• Analyzes all feasible vehicle origin-destination pairs and station locations to ensure full network coverage and zero stranding.
• Determines dynamic fuel schedules and quantities to support continuous operation across the network.
• Generates a deployment roadmap across multiple adoption scenarios to guide phased infrastructure rollout.

Experimental results

Research questions

• RQ1 What is the minimum number and optimal spatial configuration of hydrogen refueling stations required to support zero-emission MHDVs across key U.S. freight corridors?
• RQ2 How can infrastructure deployment be optimized to prevent vehicle stranding while minimizing total investment costs?
• RQ3 What role do regional freight patterns and corridor-specific traffic dynamics play in shaping cost-effective hydrogen infrastructure networks?
• RQ4 How scalable is the proposed optimization framework across different adoption scenarios and megaregions?
• RQ5 In what ways can hydrogen infrastructure deployment improve energy resilience and reduce pollution in underserved and rural communities?

Key findings

• The study identifies a minimal, strategically optimized network of hydrogen refueling stations capable of supporting 8.5% of U.S. heavy-duty freight volume across the Texas Triangle, I-10, and I-5/CA-99 corridors.
• The OR-AGENT framework successfully prevents vehicle stranding by ensuring all origin-destination pairs have viable refueling options.
• Optimal station locations are concentrated along high-volume freight corridors, with clustering near major interchanges and freight hubs.
• The genetic algorithm-based optimization reduces infrastructure costs while maintaining full network coverage and operational reliability.
• The deployment roadmap enables phased, scenario-based rollout, supporting policy and investment planning for national-scale hydrogen infrastructure.
• The framework demonstrates scalability and adaptability for nationwide application, offering a replicable model for other regions.