(633c) Techno-Economic Analysis on Near-Term and Future Projections of Levelized Cost of Hydrogen for Low-Temperature and High-Temperature Water Electrolysis Technologies

Hydrogen is seen as a potential energy intermediary between renewable energy sources and end-use applications including transportation, power, and industrial feedstocks. Core to this approach is low-cost hydrogen generation via water electrolysis. Significant research has been undertaken to improve the electrolysis stack technology, including enhancements in electrical efficiency, materials degradation, and total stack cost. However, relative to the total cost of installing an electrolysis plant, the stack contributes <50% of the initial capital investment. Therefore, from an electrolysis project perspective, the mechanical balance of plant and electrical systems required to operate the plant are equally important to understand.

To explore the near-term and future cost projection for hydrogen production via electrolysis, Strategic Analysis Inc. (SA) has developed a bottom-up project cost model for Alkaline, Proton Exchange Membrane (PEM), Anion Exchange Membrane (AEM), and Oxygen-Conducting Solid Oxide (SO) electrolysis technologies. This project cost model incorporates: 1) Stack cost, derived from a Design for Manufacturing and Assembly (DFMA) process-based cost model developed by SA, 2) mechanical balance of plant, including process equipment, piping, valves, and instrumentation, derived from equipment quotes, scaling, database values, and Aspen estimates; 3) electrical balance of plant, including wiring, rectification, and electrical infrastructure upgrades, derived from time and material cost correlations; 4) Site Preparation, focused on green field installation; and 5) Construction Overhead, including engineering, procurement, and construction (EPC) costs and project contingency. The SA project cost model is fed into a Levelized Cost of Hydrogen (LCOH) model that accounts for electricity and water consumption, in addition to other operating costs, including labor, maintenance, and stack replacements.

The SA project cost model and the LCOH model were used to conceptualize electrolysis system sizes from 100 MW to 1 GW for Alkaline, PEM, AEM, and SO electrolysis systems. From a project perspective, electricity costs contribute 50-80% to the LCOH while capital and maintenance costs contribute the remaining 20-50% to the LCOH. Improvements in stack performance and cost offer incremental improvements in LCOH; however, larger reductions in hydrogen cost will only be possible through optimization of the stack cell voltage and operating current density in conjunction with reductions in net electricity price through integration with low-cost, probably renewable, electricity.

Results from SA’s polarization performance optimization model show that lower cost Alkaline stacks, having somewhat lower performance (than PEM), tend to optimize at lower current densities leading to a larger stack active area, and benefit from low operational voltage to obtain higher conversion efficiencies. Higher cost PEM stacks with higher performance (than Alkaline stacks) tend to optimize at higher current densities to reduce the size/capital cost of the stacks and can afford a lower stack efficiency. LCOH projections for AEM suggest near-term costs are high due to low stack sizes and low manufacturing rates but have the potential to reduce in cost as the manufacturing scales up. Solid oxide systems benefit in lower stack electricity consumption at the cost of high balance of plant energy load.

Multivariable sensitivity analyses have been conducted to explore the impact of electricity prices and capacity factor on the levelized cost of hydrogen. This mapping highlights the potential for low-cost renewable electricity such as solar and wind to reduce the LCOH for electrolysis systems while accounting for the associated reduction in capacity factor. The results of this study provide guidance on where the largest incremental reductions in LCOH can be achieved on a project basis.