Cost-optimized replacement strategies for water electrolysis systems affected by degradation

TL;DR

This paper develops a linear optimization model to determine the cost-effective timing for replacing electrolyzer stacks in green hydrogen production, considering degradation and uncertainties to reduce overall costs.

Contribution

It introduces a novel linear optimization approach incorporating degradation modeling and uncertainty analysis to optimize electrolyzer replacement timing.

Findings

Optimal replacement time varies up to 9 years due to degradation uncertainty.

Degradation scale significantly impacts lifetime and costs.

Understanding degradation effects is crucial for cost reduction in hydrogen projects.

Abstract

A key factor in reducing the cost of green hydrogen production projects using water electrolysis systems is to minimize the degradation of the electrolyzer stacks, as this impacts the lifetime of the stacks and therefore the frequency of their replacement. To create a better understanding of the economics of stack degradation, we present a linear optimization approach minimizing the costs of a green hydrogen supply chain including an electrolyzer with degradation modeling. By calculating the levelized cost of hydrogen depending on a variable degradation threshold, the cost optimal time for stack replacement can be identified. We further study how this optimal time of replacement is affected by uncertainties such as the degradation scale, the load-dependency of both degradation and energy demand, and the costs of the electrolyzer. The variation of the identified major uncertainty degradation scale results in a difference of up to 9 years regarding the cost optimal time for stack replacement, respectively lifetime of the stacks. Therefore, a better understanding of the degradation impact is imperative for project cost reductions, which in turn would support a proceeding hydrogen market ramp-up.