Techno-economic evaluation of green hydrogen production with low-temperature water electrolysis technologies directly coupled with renewable power sources

•Economic analysis was performed on six combinations of renewables and electrolysis.•Levelized cost of green hydrogen was calculated with directly coupled to renewables.•Levelized cost of electricity is calculated by machine learning model of renewables.•The most economic combination of electrolysis...

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Veröffentlicht in:Energy conversion and management 2023-06, Vol.286, p.117083, Article 117083
Hauptverfasser: Shin, Haeseong, Jang, Dohyung, Lee, Sangdon, Cho, Hyun-Seok, Kim, Kyong-Hwan, Kang, Sanggyu
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Sprache:eng
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Zusammenfassung:•Economic analysis was performed on six combinations of renewables and electrolysis.•Levelized cost of green hydrogen was calculated with directly coupled to renewables.•Levelized cost of electricity is calculated by machine learning model of renewables.•The most economic combination of electrolysis and renewables was determined.•Capacity factor of renewables is the mostly affect the levelized cost of hydrogen. It is obvious that green hydrogen production needs to increase to solve climate change issues, but green hydrogen has not been actively produced due to economic disadvantages. In order to secure the economic feasibility of green hydrogen production, it is necessary to find the optimal combination of renewable power sources and water electrolysis types. In this study, the combinations of three types of renewable power plant such as offshore wind, onshore wind, and onshore photovoltaic and two types of water electrolysis such as alkaline water electrolysis (AWE) and polymer electrolyte membrane water electrolysis (PEMWE) are analyzed in the economic evaluation. Previous researches on economic evaluation of green hydrogen production have only been conducted under rated operating conditions, but this study conducted realistic calculations by considering partial load operation according to fluctuating power generation. Accurate hydrogen production efficiency was derived by using actual renewable energy generation data for year with sample time of 1hr, and water electrolysis system simulation results according to power input. The offshore wind power generation data was generated using a wind power generation prediction model using a machine learning method. LCOH for each case was calculated using cost data of system components, and the impact of each price component on LCOH was analyzed through sensitivity analysis. As a result of the calculations, the onshore wind power-AWE case has the lowest LCOH with 7.25 $/kg while PV-PEMWE case has the highest LCOH with 13.44 $/kg. The capacity factor of renewable energy is shown to have the greatest impact on LCOH by sensitivity analysis, followed by the capital expenditure (CAPEX) of the renewable power plant or the operating expenditure (OPEX). This study provides an insight to establish the methodology finding out the most efficient green hydrogen production system based on water electrolysis dedicated to renewable power sources.
ISSN:0196-8904
DOI:10.1016/j.enconman.2023.117083