Green and low-carbon hydrogen - the impact of classification rules and subsidies on asset sizing and energy sourcing for electrolytic hydrogen production.

The production of green hydrogen from renewable energy and water by electrolysis is considered an important technology for decarbonation of many industries. To improve the competitiveness of this burgeoning industry, many jurisdictions are introducing incentive programs, including Europe, the US, and Australia. Eligibility for these incentives is linked to electricity sourcing rules to promote the use of renewable and low-carbon sources. However, definitions of green and lowcarbon hydrogen vary between jurisdictions. One key difference is the measurement of temporal correlation between renewable sources and electrolyser consumption, with hourly, monthly, and yearly time-matching proposed. Furthermore, certain regions with cleaner grid mixes may have the option to produce low-carbon hydrogen without adherence to these rules. This paper studies the impact of these differing green and lowcarbon classification rules on sourcing strategy, equipment sizing, final cost, and grid emissions exposure of the produced hydrogen. A market-focused 2 -stage stochastic model of a green hydrogen producer supplying a hydrogen demand is used, with uncertainty in renewable production and electricity spot market prices. Strict hourly time-matching is observed to increase demand for diversified power purchase agreement (PPA) portfolios, and require greater electrolyser and hydrogen storage capacities. For carbon-intensive grids, less strict time matching rules can lead to the produced hydrogen being classified as 100% green whilst exceeding intended maximum emissions intensities.

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Publication Details

Published
2024-11-20
DOI
https://doi.org/10.1109/aupec62273.2024.10807631
Citations
4
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.83
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article

Green and low-carbon hydrogen - the impact of classification rules and subsidies on asset sizing and energy sourcing for electrolytic hydrogen production.

Simon Camal, Hugo Radet, Robin Girard, Owen Palmer
4 citations
Integrated Energy Systems Optimization
0.83
article

Green and low-carbon hydrogen - the impact of classification rules and subsidies on asset sizing and energy sourcing for electrolytic hydrogen production.

Simon Camal, Hugo Radet, Robin Girard, Owen Palmer
article en
4 citations

Abstract

The production of green hydrogen from renewable energy and water by electrolysis is considered an important technology for decarbonation of many industries. To improve the competitiveness of this burgeoning industry, many jurisdictions are introducing incentive programs, including Europe, the US, and Australia. Eligibility for these incentives is linked to electricity sourcing rules to promote the use of renewable and low-carbon sources. However, definitions of green and lowcarbon hydrogen vary between jurisdictions. One key difference is the measurement of temporal correlation between renewable sources and electrolyser consumption, with hourly, monthly, and yearly time-matching proposed. Furthermore, certain regions with cleaner grid mixes may have the option to produce low-carbon hydrogen without adherence to these rules. This paper studies the impact of these differing green and lowcarbon classification rules on sourcing strategy, equipment sizing, final cost, and grid emissions exposure of the produced hydrogen. A market-focused 2 -stage stochastic model of a green hydrogen producer supplying a hydrogen demand is used, with uncertainty in renewable production and electricity spot market prices. Strict hourly time-matching is observed to increase demand for diversified power purchase agreement (PPA) portfolios, and require greater electrolyser and hydrogen storage capacities. For carbon-intensive grids, less strict time matching rules can lead to the produced hydrogen being classified as 100% green whilst exceeding intended maximum emissions intensities.

Université Paris Sciences et Lettres (FR), Centre Procédés, Energies Renouvelables et Systèmes Energétiques (FR)
Openalex Percentile: Top 26%
Integrated Energy Systems Optimization
0.83
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