InfraInt – Infrastructure development model for hydrogen and CO₂

The optimization model “InfraInt” models existing pipelines, the new construction of hydrogen and CO₂ pipelines, and the repurpose of natural gas pipelines to hydrogen pipelines. In addition, the locations of electrolysis and methanation are determined in a cost-optimal way to give a complete picture of the transport infrastructure. The model integrates sources and sinks of energy-relevant gases into a holistic infrastructure. Accordingly, the name of the model is also derived from the terms “infrastructure” and “integrated”.

Context

Some of the infrastructure for transporting energy-related gases already exists today (natural gas network) or needs to be built as part of the energy transition (hydrogen, hydrogen derivatives, CO₂). The transport effort depends on the location of production and consumption. There are basically two options for the production of renewable gases:

First, production can be carried out at the plant site of renewable power generation. To transport synthetic fuels to consumption centers, pipeline-based gas infrastructure is required. For synthetic methane production, the use of captured CO₂ from industrial point sources is an option. Transport of the CO₂ to the generation facilities can again be accomplished via pipeline-based infrastructure. If the CO₂ is materially captured, it must also be transported to the consumers. Hydrogen can be fed into the existing natural gas grid to a certain extent. However, for transportation of pure hydrogen to, for example, steel industry load centers, new pipelines must be built or existing natural gas pipelines repurposed.

On the other hand, renewable fuel generation plants can be placed directly at load centers. In this case, a large part of the gas grid infrastructure would become obsolete.

What is InfraInt used for?

The model is intended to show the future expansion needs of H₂ and CO₂ pipelines in Europe. An example result for hydrogen infrastructure in 2030 is shown in Figure 1. The model indicates what capacities the pipelines must have to meet the demand of the counties. It also highlights the costs of building and operating the pipelines. The pipeline infrastructure is determined based on cost minimization, so the calculated transportation network specifies the least-cost option for pipeline-based transportation of hydrogen and CO₂. Existing plans, such as the Hydrogen Backbone are included in the model as one option of future hydrogen transport. As an additional component, the locations and production capacities of electrolysis and methanation are determined at district level and thus provide further sources and sinks of hydrogen. In particular, the location of the conversion plants provides information on whether electrolysis is placed close to generation when renewable electricity is produced, or close to consumption in counties with hydrogen demand, eliminating the need for connection through hydrogen pipelines. Again, the costs of electrolysis and methanation can be evaluated depending on their capacity.

How does InfraInt work?

Input data regionalized at district level:

• Electricity demand and electricity supply from renewable energies to indicate the availability of electricity for electrolysis on site
• Hydrogen demand from the transport, buildings, industry and reconversion sectors
• Demand for SynFuel and SynGas
• CO₂ capture from industry
• Model of the existing natural gas transportation network
• Model of the hydrogen backbone as a possible secondary condition
• Hydrogen/ammonia imports by pipeline and ship

A cost function is determined in which the following factors are included:

• Costs for the construction of new pipelines depending on length and capacity (investment and operation)
• Costs for the conversion of natural gas pipelines to hydrogen pipelines
• Costs for electrolysis depending on the production capacity
• Costs for methanation depending on capacity
• Costs for cracking imported ammonia
• Electricity grid costs for the purchase of electrolysis electricity from the electricity grid
• Costs for capturing CO₂ from the air and at industrial point sources
• Costs for methanation and electrolysis

When minimizing the cost function, the following constraints must be met:

• Covering the demand for hydrogen in each district
• Covering the demand for SynFuel and SynGas in each district
• Captured CO₂ must be stored or used
• Limitation of gas flows through pipeline capacities

Technical details

The model corresponds to a node-edge model, where the nodes represent the centers of counties and the edges represent connections between counties, which can be connected by a pipeline. The coverage of hydrogen and CO₂ demands by the modeled infrastructure is considered at the temporal resolution of one year.

The cost minimization corresponds to a mixed-integer linear optimization. The integer nature is necessary to represent the binary decision to build a pipeline connection, which only makes sense once a certain pipeline capacity is reached. Due to the inclusion of the binary variables, the cost function cannot be represented in a purely linear way and is thus much more difficult to solve. Currently, optimality gaps of about 1 % are reached. The model is implemented in Python and uses  the solver Gurobi for optimization.

History

The model was created in a simplified form in 2019 as part of a master’s thesis. In the hydrogen lead project TransHyDE Project Sys – System Analysis for Transport Solutions for Green Hydrogen, it will now be further developed in 2022. The focus here is on the calculation of a hydrogen network that is needed for the hydrogen requirements of the players.

More Information

• What Might Germany’s Future Hydrogen Infrastructure Look Like?