A New Transportation Route Planning Method for Wind-Based Hydrogen Supply Chains

Hydrogen offers options for the transition to low-carbon energy systems. Temporal and spatial gaps exist between hydrogen production and utilization, necessitating infrastructure like storage and transportation for bridging. The challenge in optimizing hydrogen supply chains (HSCs) for transportation path planning lies in efficiently solving the complex network topology. This work presents a mathematical model of two-layer optimization based on Genetic Algorithm (GA) and graph theory. Transportation route planning and wind farm selection are integrated to meet the hydrogen demand of hydrogen fuel vehicles (HFVs) over a period of time. The model enables the extraction of geographic information data and visualization of the optimal layout using ArcGIS software. Vehicle transportation and pipeline route hybrid transportation system based on Minimum Euclidean Steiner Tree (MEST) are obtained. The goal is to obtain the minimum total annual cost (TAC). Taking Fujian Province of China as an example, the feasibility of the method is verified, and the calculation results show that the total transportation cost of the method is reduced by 9.2%. The new model can provide guiding schemes for future hydrogen infrastructure construction.