Sensitivity-based techno-economic assessment approach for electrolyzer integration with hybrid photovoltaic-wind plants for green hydrogen production

This study aims to provide a Python-based modeling approach that thoroughly analyzes large-scale PV-Wind-based hydrogen production plants under two scenarios: net metering and islanded mode for PV, Wind, and PV-Wind Hybrid Renewable Energy Systems (HRES). A comprehensive techno-economic model was developed using Python, considering electrolyzer size and corresponding full loading hours, partial loading hours, and excess energy. Additionally, sensitivity analysis was conducted to assess the viability and economic feasibility of investing in green hydrogen, accounting for key parameter changes due to technological advancements or location changes. The key parameters analyzed included the Levelized Cost of Energy (LCOE) for PV and wind, electrolyzer cost, electrolyzer efficiency, electrolyzer, and stack lifetime hours. The scenarios with net metering policy recorded the lowest possible Levelized Cost of Hydrogen (LCOH) compared to islanded modes. The PV scenario with net metering achieved an LCOH of $3.79/kg at average parameter values. The PV-Wind net metering scenario achieved an LCOH of $3.97/kg with the optimal electrolyzer size. Despite the slightly higher LCOH, the PV-Wind net metering scenario yields the maximum quantity of hydrogen production. The sensitivity analysis revealed that LCOE and electrolyzer cost are the most influential factors. Reducing these top influencing parameters in combination with favorable changes in other parameters could enable the LCOH to fall to nearly $1/kg in the future in renewable energy-abundant areas if net metering policy was employed.