Techno-economical Optimization of Green Hydrogen Production with Renewable Energy Systems

Abstract

The future of the planet is at stake; for reasons, pollution of all kinds exacerbates the effects of climate change. Using renewable energy and energy carriers such as green hydrogen are advocated to be the most reliable solution. However, the technologies are still expensive and their performances are dependent on meteorological parameters making green hydrogen less cost-competitive. Depending on the location and the resources available, some renewable energy systems are more suitable to provide hydrogen at lower prices. Therefore, it is necessary to build a techno-economical optimization model that determines among several sets of renewable energy systems (Land PV, floating PV and hybrid land PV-Wind and floating PV-Wind) and electrolyser technologies (Alkaline electrolyzer, proton exchange membrane electrolyser and solid oxide electrolysis cells), the optimal configuration that gives a lower levelized cost of hydrogen. To achieve this goal, we use the COMANDO energy system optimization framework (ESOF) within which we have modelled the components and the energy and formulated optimization problem. With the Gurobi optimizer, we got the optimal results which are used to calculate the levelized cost of hydrogen and perform the sensitivity analysis. The results show that the land PV coupled with alkaline electrolyser gives the lowest cost of hydrogen with 5.926€/kgH2 followed by the floating photovoltaic coupled with alkaline electrolyser with 6.038€/kgH2. By selling the oxygen produced at 0.5€/kgO2, the levelized cost of hydrogen could drop by 41.4% to 66.2% depending on the energy system reaching 2.02€/kgH2 to 5.62€/kgH2. The carbone emission per kilogram of hydrogen produced ranged between 24.17 to 34.07 g/kgH2 which is far below the threshold set to 1kgCO2/kgH2 by the Green Hydrogen Organisation. Furthermore, for the floating photovoltaic, the water savings from evaporation is evaluated to be around 6.08 to 8.506 million cubic meters per year. The sensitivity analysis shows that among the parameters, the discount rate, the electrolyser efficiency and the total installed costs of the components are more impactful on the cost of hydrogen. Notwithstanding the details considered in this study, other aspects could be considered in the modelling such as the integration of the alternative direct current power network as well as the hydrogen flow network. The accuracy and updated costs could be the subject of further investigations to get more accurate results.