Hydrogen and SNG demand in Austrian industry

Future projections and economic aspects




The further development of the national and international energy system is characterized by the energy, environmental and climate policy paradigm of the necessary reduction of global greenhouse gas emissions. To ensure this, the gases used in the industrial sector must also be produced from renewable energy sources, like H2 or SNG from the power-to-gas technology. In many industrial applications, fossil natural gas is used as an energy source, which can be directly replaced by renewable SNG without changing the processes. In addition, it is possible to modify existing industrial processes or to develop new ones to use renewable hydrogen or SNG as an energy source, e.g. in steel industry - blast furnace process (energy carrier coke) vs. direct reduction (energy carrier hydrogen).
In Austria, the whole industry sector represents a significant economic factor with a share of about 30 % of the total gross value added [1]. To ensure this economic performance, the final energy consumption of the industry sector in Austria in 2018 was about 90 TWh, which is about 30 % of the total final energy consumption, thus high amounts of renewable gasses are necessary to decarbonize the industry sector in Austria.


The objective of the Austrian part of the project SuperP2G is to analyse the future demand of renewable H2 and SNG for the industry in the Austrian model region WIVA P&G, including aspects of cost development based on existing tools CoLLeCT, PResTiGE, and MOVE.


For estimating the future demand for PtG-products in the industry sector in Austria, comprehensive literature review concerning (among others):

  • development of the energy demand
  • potential fields of applications for renewable gases
  • emission reduction targets
  • identification of processes that cannot be electrified and still must be operated with gas

has been done. Additionally, discussions with respective stakeholders took place.

The estimation of future costs of renewable gases (H2 and SNG) are carried out mainly with the three tools CoLLeCT, PResTiGE, and MOVE, developed by the Energieinstitut an der JKU Linz.

In general, the tools are used:

  • CoLLeCT to estimate future investment costs for power-to-gas plants
  • PResTiGE to calculate the specific cost for production of the renewable gases,ans
  • MOVE to analyse the effects of respective changes on a macro-economic level.

Results: Future industry demand of renewable hydrogen and SNG

Total demand for renewable gases in Austria in 2040 , is estimated with:

  • Hydrogen demand about 60 TWh

    • Chemical industry (about 47 %)
    • Steel industry (about 38 %)
  • There is a need for 4,5 TWh SNG

    • Steel industry (about 73 %)
    • Chemical industry (about 27 %)

alt text Figure 1: Hydrogen demand in industry 2040 (acc. to Austrian Hydrogen Strategy).

alt text Figure 2: SNG demand in industry 2040 (acc. to Austrian Hydrogen Strategy).

By 2040 the demand for gaseous energy carriers in the industry sector remains the same, however there is a shift from the use of natural gas to renewable hydrogen (see Figure below).

alt text Figure 3: Current and future demand in industry 2040.

Results: Aspects of cost developments

As shown in Figure 1 power-to-gas technologies, and in particular electrolysis, are expected to have high potentials for cost reduction owing to technological learning and scaling. However, the enablement of these cost reductions is bound to an actual implementation of the considered capacities. Same applies to the speed of cost decrease: while recent studies on scaling of power-to-gas technologies consider a rather early and steep growth of global electrolysis capacities, Figure 1 (left) shows that an implementation of national or regional targets, such as the EU hydrogen strategy may even outperform these. Furthermore, a potential technological breakthrough, such as an early industrialization of solid oxide electrolysis, which is expected to achieve electric efficiencies of > 90%, may lead to even faster cost reductions, as well as a technology switch from up to now established technologies (see right part of Figure 4).

alt text Figure 4: Estimated ranges for cost reduction based on technological learning of electrolysis for global industrial deployment scenarios related to electric input power (left) and to hydrogen output with developing efficiencies (right). Based on and updated from Böhm, et al. (2022) [2]

The production costs for renewable hydrogen by electrolysis depend on a variety of parameters which are in turn dependent on other parameters, such as electrolysis technology, the performance of the electrolysis technology, mode of operation, location of the plant, year of installation, future development of costs, and technology. The hydrogen production costs calculated from one data set thus represent only one specific case. With the help of a sensitivity analysis, the influence of the individual parameters on the hydrogen production costs can be estimated, see for example Figure 5.

alt text Figure 5: Sensitivity analysis - H2 production costs (Source: Energieinstitut an der JKU Linz) Reference case: Year 2030; renewable energy ource: wind, full-load hours 3,200 h/a; PEM electrolyser; nominal power 100 MWel; efficiency electrolyser: 67.5 %; investment costs PtG plant: 20 Mio. €; electricity price: 37 €/MWh; hydrogen production costs: 5,1 €/kg

Accordingly, the full load hours, the efficiency, the investment costs, and the electricity price have a comparatively high influence on hydrogen production costs. For example, an increase of the full load hours by 10 % (e.g. building the electrolysis plant at a more optimal wind power site) would result in a reduction of the production costs of about 9 %. Further, a reduction of the electricity price by 10 %, would result in a reduction of the hydrogen production costs by about 4 %. In order to show the range of possible H2 production costs, a parameter variation was carried out. The results are shown in Figure 6.

alt text Figure 6: Range of hydrogen production costs due to parameter variation. (Source: Energieinstitut an der JKU Linz) Parameter variation: renewable energy sources: PV, Wind; full-load hour: 3 different sites; electricity costs: +/- 20%; electrolyzer technology: AEC, PEMEC, SOEC; investment costs: +/- 20 %; Efficiency of Electrolyzer: +/- 5 %; results in 486 cases per year

In the year 2030 the hydrogen production costs for a 100 MW electrolyzes plant in Europe will be in a range of about 4 to 23 €/kg, depending on the plant site and development of future investment costs, electricity prices, technology performance, and operation strategies. For the most part, however, production costs will be in the range of €9/kg in 2030, €5/kg in 2040, and €4 in 2050.


Hydrogen Production Cost

0.0 €/kg

alt text


  • The most influencing parameter on the hydrogen production costs are the electricity costs.
  • Influence of the full load hours of the electrolyzer - should be operated with at least 4,000 full load hours (here the influence of CAPEX and OPEX decreases significantly).
  • The use of by-products (excess heat and oxygen) must be forced.

See Figures 7 and 8.

alt text Figure 7: Specific hydrogen production cost in 2030 with a 60 MWel electrolyzer at different electricity prices (Source: Energieinstitut an der JKU Linz)

alt text Figure 8: H2 production cost estimates with a 60 MW PEM electrolyzer in 2030 (electricity costs 60 €/MWh) depending on the annual full load hours (Source: Energieinstitut an der JKU Linz)


[1] WKO, 2021. Wertschöpfung nach Sektoren [online]. Beiträge zur Gesamtwertschöpfung. Verfügbar unter: http://wko.at/statistik/eu/europa-wertschoepfung.pdf

[2] BMK/BMAW, Hydrogen Strategy for Austria (2022) p. 12 (available under: https://www.bmk.gv.at/dam/jcr:0eb2f307-1e4d-41b1-bfd8- 22918816eb1b/BMK_Wasserstoffstrategie_DE_UA_final.pdf ).

[3] Baumann et al., 2021 “Erneuerbares Gas in Österreich 2040: Quantitative Abschätzung von Nachfrage und Angebot.”

[4] Böhm (2022), "Techno-economic assessment of emerging power-to-gas technologies using advanced generic methods", Dissertation, Leoben, 2022, doi: 10.13140/RG.2.2.30028.90248


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