Optimal Green Hydrogen Production and Transportation: Africa to Europe

This paper presents an optimization framework for green hydrogen (GH) production, which integrates the operation of subsystems consisting of photovoltaic generation, reverse-osmosis desalination, proton exchange membrane electrolysis, and battery energy storage for continuous operation under solar intermittency. A two-step Ordinal Optimization (OO) method is used to explore efficiently the large design search space and identify subsystem sizes that minimize the levelized cost of hydrogen ($/kg), including production, storage, and transportation. First, the designs are evaluated using a simple but computationally efficient model based on a two-week simulation. The evaluated designs are then scaled to a yearly operation and ranked by increasing hydrogen costs. Second, the top-S designs are reevaluated using an accurate annual simulation model. OO theory predicts the number of top-S designs that need to be evaluated accurately to ensure that the optimum is included with a 95% alignment probability. This framework was applied to case studies for producing GH for local use in Tunis at a cost of $2.945, and for shipping to Genoa, Italy, and to Hamburg, Germany, at costs of $3.902 and $6.382 per kg, respectively. The study leverages the potential of renewable energy (RE) production in Tunis and its proximity to Europe.

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Publication Details

Journal
Energies
Published
2026-08-03
DOI
https://doi.org/10.3390/en19153649
Primary Topic
Hybrid Renewable Energy Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimal Green Hydrogen Production and Transportation: Africa to Europe

Amal Asaad, Sami Karaki
Energies
Hybrid Renewable Energy Systems
article

Optimal Green Hydrogen Production and Transportation: Africa to Europe

Amal Asaad, Sami Karaki
article en

Abstract

This paper presents an optimization framework for green hydrogen (GH) production, which integrates the operation of subsystems consisting of photovoltaic generation, reverse-osmosis desalination, proton exchange membrane electrolysis, and battery energy storage for continuous operation under solar intermittency. A two-step Ordinal Optimization (OO) method is used to explore efficiently the large design search space and identify subsystem sizes that minimize the levelized cost of hydrogen ($/kg), including production, storage, and transportation. First, the designs are evaluated using a simple but computationally efficient model based on a two-week simulation. The evaluated designs are then scaled to a yearly operation and ranked by increasing hydrogen costs. Second, the top-S designs are reevaluated using an accurate annual simulation model. OO theory predicts the number of top-S designs that need to be evaluated accurately to ensure that the optimum is included with a 95% alignment probability. This framework was applied to case studies for producing GH for local use in Tunis at a cost of $2.945, and for shipping to Genoa, Italy, and to Hamburg, Germany, at costs of $3.902 and $6.382 per kg, respectively. The study leverages the potential of renewable energy (RE) production in Tunis and its proximity to Europe.

EnergiesVol. 19(15)
American University of Beirut (LB)
American University of Beirut
Affordable and clean energy
Openalex Percentile: Top 22%
Hybrid Renewable Energy Systems
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