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https://dx.doi.org/10.48550/ar...
Article . 2023
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Ramping up the hydrogen sector: An energy system modeling framework

Authors: T. Klatzer; U. Bachhiesl; S. Wogrin; A. Tomasgard;

Ramping up the hydrogen sector: An energy system modeling framework

Abstract

With the transition towards a decarbonized society, energy system integration is becoming ever more essential. In this transition, the energy vector hydrogen is expected to play a key role as it can be produced from (renewable) power and utilized in a plethora of applications and processes across sectors. To date, however, there is no infrastructure for the production, storage, and transport of renewable hydrogen, nor is there a demand for it on a larger scale. In order to link production and demand sites, it is planned to re-purpose and expand the existing European gas pipeline network in the future. During the early stages of ramping up the hydrogen sector (2020s and early 2030s), however, blending natural gas with hydrogen for joint pipeline transmission has been suggested. Against this background, this paper studies hydrogen blending from a modeling perspective, both in terms of the implications of considering (or omitting) technical modeling details and in terms of the potential impact on the ramp-up of the hydrogen sector. To this end, we present a highly modular and flexible integrated sector-coupled energy system optimization model of the power, natural gas, and hydrogen sectors with a novel gas flow formulation for modeling blending in the context of steady-state gas flows. A stylized case study illustrates that hydrogen blending has the potential to initiate and to facilitate the ramp-up of the hydrogen sector, while omitting the technical realities of gas flows -- particularly in the context of blending -- can result in suboptimal expansion planning not only in the hydrogen, but also in the power sector, as well as in an operationally infeasible system.

66 pages

Keywords

Optimization and Control (math.OC), FOS: Mathematics, Mathematics - Optimization and Control

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Average
Average
Top 10%
Related to Research communities
Energy Research