Issue 7, 2019

Projected economic outlook and scenario analysis for H2 production by alkaline water electrolysis on the basis of the unit electricity price, the learning rate, and the automation level

Abstract

H2 is regarded as an alternative to current energy carriers without CO2 emission. To supplement traditional H2 production by fossil fuels, alkaline water electrolysis (AWE) is back in the spotlight. Unfortunately, H2 production by AWE is not economically practical yet compared with current fossil fuel H2 production methods. In this context, scenario analysis was performed in this study to find a suitable and reasonable scenario in which AWE is cost-competitive in terms of the levelized cost of H2 (LCOH) on the basis of diverse economic parameters such as the unit electricity price, the learning curve, and the automation level. From scenario analysis results, it is identified that the unit electricity price is the most effective economic factor to determine the LCOH followed by the learning curve and the automation level demonstrating that the introduction of surplus electricity, inevitably generated from renewable sources, can be very crucial for H2 production from AWE to be economically viable compared with the estimated LCOH of 1.25 USD per kg H2 in 2030 targeted by the United States Department of Energy. Most importantly, it can provide technical and economic guidelines on the basis of scenario analysis results. This can be very useful for decision makers to make economic and environmental policies in Korea and will result in entering the H2 economy society in the near future.

Graphical abstract: Projected economic outlook and scenario analysis for H2 production by alkaline water electrolysis on the basis of the unit electricity price, the learning rate, and the automation level

Article information

Article type
Paper
Submitted
09 Mar 2019
Accepted
18 Apr 2019
First published
30 May 2019

Sustainable Energy Fuels, 2019,3, 1799-1807

Projected economic outlook and scenario analysis for H2 production by alkaline water electrolysis on the basis of the unit electricity price, the learning rate, and the automation level

B. Lee, H. Lee, H. Cho, W. Cho, C. Kim and H. Lim, Sustainable Energy Fuels, 2019, 3, 1799 DOI: 10.1039/C9SE00148D

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