Long-term optimization of the hydrogen-electricity nexus in France: Green, blue, or pink hydrogen?

Research output: Contribution to journalArticlepeer-review

Abstract

We model the optimal hydrogen and electricity production and storage mix for France by 2050. Moreover, an iterative calculation method to represent electrolyzer lifetime based on functioning hours in linear programming is developed. We provide a central scenario and study its sensitivity to the cost of electrolyzers, to hydrogen demand and to renewable energy deployment potential. The proportion of electrolysis to methane reforming with CO2 capture and storage in hydrogen production is sensitive to the cost of electrolyzers, with the former providing around 60% in the central scenario. However, the system cost as well as the hydrogen and electricity production costs are much more robust, thanks to the wide feasible near-optimal solutions spectrum. The electricity production mix is almost fully renewable in the central scenario, while nuclear power has a significant role only if the potential of wind & solar limits their deployment, or if CO2 capture and storage is not authorized. Furthermore, exclusion of reformer-based hydrogen from fossil gas with CO2 capture induces negligible additional cost to the hydrogen-electricity coupled system (below 1%). Therefore, in the current European resilience and sovereignty context, a robust low-carbon hydrogen development strategy would be prioritizing green hydrogen to other low-carbon hydrogen supply options.

Original languageEnglish
Article number113702
JournalEnergy Policy
Volume181
DOIs
Publication statusPublished - 1 Oct 2023
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Blue hydrogen
  • Electricity markets
  • Green hydrogen
  • Large-scale renewable integration
  • Levelized cost of hydrogen
  • Low-carbon hydrogen
  • Optimization
  • Power system modelling
  • Prospective planning
  • Renewable energies

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