Abstract
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.
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