Planning Green Hydrogen Production and Transportation

Planning Green Hydrogen Production and Transportation

GHD is one of the world’s leading professional service companies operating in the global markets of water, energy, resources, and transportation. They provide digital engineering services to private and public sector clients. One of their areas of expertise is green hydrogen supply chain simulation.

Green hydrogen is made from splitting water using electrolysis powered by renewable energy, thus avoiding carbon production. When mixed with nitrogen, green hydrogen can be more easily transported over long distances by ships. However, the expenditures for plant design, logistics, market research, risk assessment, and other factors are not always apparent, and the uncertainty of levelized hydrogen production and transportation costs often become the main reasons for stopping the project.

To evaluate the feasibility of such projects from both the engineering and financial sides, GHD applies green hydrogen supply chain simulation. This helps them link engineering design scenarios directly to business values. Unlike spreadsheet modeling, dynamic simulation better captures the complexity and risks, visualizes processes, as well as accounts for the projects’ economics. Simulation models allow executives to interact with digital replicas of the projects and make more intelligent decisions.


An Australian company needed to build a green hydrogen production plant and a supply chain that would be financially and technologically efficient. Instead of building static green hydrogen logistics models, they hired GHD, who used a combination of traditional engineering design and dynamic simulation to:

GHD chose AnyLogic as a simulation tool for the following reasons:


In the model, the production process takes raw inputs – desalinated water, air, and electricity – going to the electrolyzer plants, where different technology selections for hydrogen production are applied. Then, the hydrogen is compressed and goes to the ammonia plant where hydrogen is synthesized with nitrogen for easier transportation.

Green hydrogen production supply chain

Cashflow analysis for the green hydrogen production supply chain (click to enlarge)

The precise simulation of gas production and storage was possible thanks to the AnyLogic Fluid Library. It easily captured various characteristics of flows, such as rate and throughput, to find possible bottlenecks and downtimes, and optimize operational processes. To simulate flows’ behaviors, the library used the discrete rate simulation approach. This made the modeling process more transparent and allowed users to track flow changes when they took place.

The viable options for hydrogen and ammonia logistics were also simulated, including modes of transportation and cost per km/kg, required assets, and enabling infrastructure. The cost of enabling port infrastructure to export ammonia was also considered.

Power load and power supply in the green hydrogen supply chain

Power load and power supply in the green hydrogen supply chain (click to enlarge)

To post-process the outputs and provide detailed cashflow analysis, the Python integration capabilities of AnyLogic were used. They extended the green hydrogen supply chain simulation with the financial model which included statistics for cashflows, NPVs, levelized costs, ROIs, and other financial metrics. They visualized the analytics using dashboards so that the management could compare scenarios and look at the value changes over time.

The production and transportation green hydrogen model allowed the engineers to:

Green hydrogen supply chain model - a breakdown
Green hydrogen supply chain model - a breakdown


The green hydrogen supply chain model was used to:

The supply chain model combined different workstreams and allowed users to see how each stream affected the green hydrogen end-to-end lifecycle and different parts of the supply chain. It helped link engineering scenarios to business outcomes, which resulted in better planning and enterprise decision management. The simulation also brought more clarity into the interconnected processes, as well as captured uncertainty and variability, which is impossible with static models.

Although production of hydrogen at the needed cost is currently beyond reach, possible pathways to this goal were found. And the model assumptions can easily be updated as new information becomes available and costs reduce over time.

This case study is from a presentation given by Geoff Martin, Technical Lead of Simulation Analytics & Strategic Insights team, at theAnyLogic Conference 2021:

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