An innovative approach to estimating green hydrogen production costs

Abstract

Green hydrogen production employs various methods, using wind, solar, and wave energy sources which draw particular attention. However, the costs of green hydrogen production vary depending on geographic location. This study aims to achieve location-independent green hydrogen production costs. For this purpose, empirical equation models for green hydrogen production costs are proposed for the first time. The estimation of these model parameters have been performed using the Modified Particle Swarm Optimization Algorithm. This algorithm has been employed here for the first time due to its advantages. Results indicate that the costs of green hydrogen produced by wind power plant, solar power plant, and wave energy converter can be estimated with average errors of 7.02%, 2.30%, and 0.01%. In addition, the standard deviation values were calculated as 10.73, 3.64 and 0.02, respectively. This finding demonstrates that green hydrogen production costs can be predicted with high accuracy case studies conducted in different locations, supporting the obtained results. Additionally, the findings indicate that wind speed in wind power plant, global horizontal irradiance in solar power plant, as well as wave power density and wind speed in wave energy converter, significantly reduce the cost of green hydrogen production.