Optimizing interoperable hydrogen supply chain design: A case study in Auvergne-Rhône-Alpes

Hydrogen (H2) is considered one of the main pillars for transforming the conventional “dark” energy system to a net-zero carbon or “green” energy system. This work reviewed the potential resources for producing low-carbon hydrogen in China, as well as the possible hydrogen production methods based on the available resources. The analysis and comparison of the levelized cost of hydrogen (LCOH) for different hydrogen production pathways, and the optimal technology mixes to produce H2 in China from 2020 to 2050 were obtained using the mixed-integer linear programming (MILP) optimization model. The results were concluded as three major ones: (a) By 2050, the LCOH of solar- and onshore-wind-powered hydrogen will reach around 70–80 $/MWh, which is lower than the current H2 price and the future low-carbon H2 price. (b) Fuel costs (>40%) and capital investments (~20%) of different hydrogen technologies are the major cost components, and also are the major direction to further reduce the hydrogen price. (c) For the optimal hydrogen technology mix under the higher renewable ratio (70%) in 2050, the installed capacities of the renewable-powered electrolysers are all more than 200 GW, and the overall LCOH is 68.46 $/MWh. This value is higher than the LCOH (62.95 $/MWh) of the scenario with higher coal gasification with carbon capture and the storage (CG-CCS) ratio (>50%). Overall, this work is the first time that hydrogen production methods in China has been discussed comprehensively, as well as the acquisition of the optimal H2 production technology mix by the MILP optimization model, which can provide guidance on future hydrogen development pathways and technology development potential in China.

This study investigates the optimal design of low-carbon hydrogen supply chains on a national scale. We consider hydrogen production based on several feedstocks and energy sources, namely water with electricity, natural gas and biomass. When using natural gas, we couple hydrogen production with carbon capture and storage. The design of the hydrogen, biomass and carbon dioxide (CO2) infrastructure is performed by solving an optimization problem that determines the optimal selection, size and location of the hydrogen production technologies, and the optimal structure of the hydrogen, biomass and CO2 networks. First, we investigate the rationale behind the optimal design of low-carbon hydrogen supply chains by referring to an idealized system configuration and by performing a parametric analysis of the most relevant design parameters of the supply chains, such as biomass availability. This allows drawing general conclusions, independent of any specific geographic features, about the minimum-cost and minimum-emissions system designs and network structures. Moreover, we analyze the Swiss case study to derive specific guidelines concerning the design of hydrogen supply chains deploying carbon capture and storage. We assess the impact of relevant design parameters, such as location of CO2 storage facilities, techno-economic features of CO2 capture technologies, and network losses, on the optimal supply chain design and on the competition between the hydrogen and CO2 networks. Findings highlight the fundamental role of biomass (when available) and of carbon capture and storage for decarbonizing hydrogen supply chains while transitioning to a wider deployment of renewable energy sources.

A mixed integer linear programming (MILP) model for the optimal design and operation of a hydrogen supply chain (HSC) under CO 2 emission constraints is presented. The mathematical model includes carbon capture and storage (CCS) methods and carbon tax as CO 2 mitigation strategies. A case study of a future hydrogen supply chain in the United Arab Emirates (UAE) is analyzed. The optimization objective consists of the minimization of the total network cost, both in terms of capital and operating expenditures, under techno-economic and environmental constraints. The optimization problem was formulated in the General Algebraic Modeling System (GAMS®). The aim of this work is to determine the optimal design and operation of a future hydrogen supply chain in the United Arab Emirates with and without CO 2 emission regulations. Also, the model determines the most suitable delivered product form (i.e., gaseous or liquid) into the market. The optimization results show that the mathematical model is a valuable tool for designing the optimal hydrogen supply chain of the country, minimize the supply chain costs, and reduce the CO 2 emissions.

Multi-period hydrogen supply chain planning for advancing hydrogen transition roadmaps

Hydrogen supply chain for future hydrogen-fuelled railway in the UK: Transport sector focused

Integration of high levels of electrolytic hydrogen production: Impact on power systems planning

Multi-objective optimization of a hydrogen supply chain network: Wind and solid biomass as primary energy sources for the public transport in Sicily

One of the proposed strategies to reach net-zero goals is the diversification of a country�s energy mix and transition to technologies that favour the mitigation of greenhouse gas emissions, while decreasing dependency on conventional fuels. This work presents a mathematical model that describes key production routes for two proposed energy transition vectors, biomethane and hydrogen, expressed as a Mixed-Integer Linear Problem (MILP). The supply chain is optimized with the objective of maximizing the profits from the global supply chain. The problem is formulated as an allocation problem, with production distributed between biomethane and hydrogen markets. The case study focuses on a region in Mexico where second-generation biomass for biogas production is abundant, while hydrogen is produced from biomethane using steam methane reforming. The results highlight the importance of balancing resource allocation in shared supply chains. With a production ratio of 60% biomethane and 40% hydrogen, a Levelized Cost of Hydrogen (LCOH) of 2.07 �/kWh and a Levelized Cost of Biomethane (LCBM) of 0.17 �/kWh are obtained, resulting in total hydrogen and biomethane production of 12,563 GWh/year and 72,374 GWh/year, respectively.

• Decarbonizing heat-intensive industries in water-scarce regions. • Green H 2 supply chains linked to local renewable energy sources. • Using underused desalination water for hydrogen production. • MILP model implemented in Julia, solved with Gurobi optimizer. • Projected LCOH $2.18/kg and 1.6 Mt CO 2 avoided annually. Achieving global decarbonization is essential to mitigate climate change, yet heat-intensive industries remain challenging to decarbonize through electrification alone. Green hydrogen offers a clean alternative to replace fossil fuels and fossil fuel–based hydrogen, but its deployment requires careful planning and robust economic assessment. This study addresses the optimal design of a green hydrogen supply chain in a Mediterranean region where ceramics and cement dominate as energy-intensive industries, while oil refining is the main consumer of fossil fuel–based hydrogen. The region also faces freshwater scarcity due to its climate and the high demand for water from tourism and agriculture. A Mixed-Integer Linear Programming (MILP) model is developed to minimize the total cost of supplying green hydrogen by determining the optimal size and location of renewable energy sources, integrating desalinated seawater from existing desalination plants as feedstock, and designing the infrastructure connecting production, storage, and demand centers. The cost-optimal configuration includes 3.4 GW of PEM electrolyzers requiring 41.1 m 3 /h of desalinated seawater supplied by existing desalination plants, along with 5.1 GW of wind and 12 GW of solar power as renewable energy sources for large-scale hydrogen production. Results show that supplying green hydrogen to these industries can avoid approximately 4.4 million tons of CO 2 emissions annually, achieving a levelized cost of hydrogen (LCOH) of $2.18/kg for the period 2030–2050. Beyond this case study, the proposed framework provides a replicable methodology for planning hydrogen-based energy systems in regions facing similar water and decarbonization challenges.

Techno-economic evaluation of green hydrogen supply chain integrated with multi-selling strategies

Techno-economic and environmental assessment of LNG export for hydrogen production

Techno-economic and life-cycle assessment of hydrogen production pathways in the Middle East and North African region

Aiming to mitigate the environmental impact derived from fossil fuels, we propose an integrated carbon capture-biomass gasification process is proposed to produce low-carbon hydrogen as an alternative energy carrier. The process begins with the pre-treatment of empty fruit bunches (EFB), involving grinding, drying, torrefaction, and pelletization. The resulting EFB pellet is then fed into a dual gasifier, followed by a catalytic cracking of tar and water gas shift reaction to produce syngas, aiming to increase its H2 to CO ratio. Subsequently, we explore two alternatives (DEPG and MEA) for syngas upgrading by removing CO2. Finally, a PSA system is modeled to obtain H2 at 99.9% purity. The pre-treatment stage densifies the biomass from an initial composition (%C 46.47, %H 6.22, %O 42.25) to (%C 54.10, %H 6.09, %O 28.67). The dual gasifier operates at 800�C, using steam as a gasifying agent. The resulting syngas has a volume concentration (%CO 20.0, %CO2 28.2, %H2 42.2, %CH4 5.9). Next stages of the process focus on removing the CO2 and increased H2 through catalytic reactions from the syngas. Thus, the DEPG carbon capture process can decrease the CO2 concentration to 2.9%, increasing the hydrogen to 95.6% in volume. In contrast, the MEA process reduces the concentration of CO2 to 5.2% and increases the concentration of H2 to 93.1%. Moreover, we estimate a levelized costs of hydrogen (LCOH) and carbon capture cost for each method (DEPG and MEA) (LCOC) and CO2 avoided (LCCA). LCOH: 3.05 USD/kg H2, LCOC: 92 and 59 USD/t CO2 and 183 and 119 USD/t CO2, for DEPG and MEA respectively.

Hydrogen is seen as a key energy vector in future energy systems due to its ability to be stored in large volumes for long periods, providing energy flexibility and security. Despite the importance of storage in hydrogen's potential role in a zero-carbon energy system, many techno-economic analyses fail to adequately model different storage methods in hydrogen supply chains, often ignoring storage requirements altogether. Therefore, this paper uses a data-driven techno-economic analysis (TEA) tool to examine the effect of storage size and cost on three different 2030 hydrogen supply chain scenarios: wind-based, solar-based, and mixed-source grid electrolysis. For varying storage sizes and specific capital costs, the overall levelised cost of hydrogen (LCOH), including production, storage, and delivery to a constant demand, varies significantly. The LCOH ranges from €3.90–12.40/kgH2, €5.50–12.75/kgH2, and €2.80–15.65/kgH2 for the wind-based, solar-based, and mixed-source grid scenarios respectively, with lower values for scenarios with low-cost storage. This highlights the critical role of low-cost hydrogen storage in realising the energy flexibility and security electrolytic hydrogen can provide.

Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) for Optimal Design of Hydrogen Supply Chains