Techno-economic analysis and Monte Carlo simulation for green hydrogen production using offshore wind power plant

•Techno-economic analysis was performed on hydrogen production by offshore wind power.•Net Present Value, sensitivity analysis, and the Monte Carlo method were undertaken.•Numerical model was integrated to derive the performance of the electrolysis system.•Distributed case was found to be the most feasible followed by centralized case.•Capacity factor was the most influential variables for Levelized Cost of Hydrogen. With the growth of marine energy such as offshore wind power, hydrogen is a promising solution for the intermittence of renewable energy sources and long-distance transmission. Some demonstration projects of offshore hydrogen production are underway using wind power. However, comparative studies on novel options such as individual hydrogen production and transport to land from each wind turbine, have not advanced beyond conceptual suggestion. In this study, to determine the most economical method of connecting offshore wind power plants and hydrogen production facilities, a techno-economic analysis of three offshore wind power plant arrangements is presented, including distributed hydrogen production, centralized hydrogen production, and onshore hydrogen production. As a method for feasibility comparison, net present value calculation, sensitivity analysis, and Monte Carlo simulation are suggested and analysis results for three arrangements are presented. In particular, the results of the proton exchange membrane electrolysis system model that is developed in the previous study are applied in order to determine the hydrogen production efficiency. Calculated hydrogen production cost was 13.81, 13.85, 14.58 $/kgH2 for distributed case, centralized case, and onshore hydrogen production case, respectively. The analysis results show that distributed case has the most competitive case due to the absence of expensive High Voltage Direct Current cable and offshore substation. Sensitivity analysis shows it is necessary to maintain capacity factor.