Uncertainty and ambiguity in techno-economic analysis : A case study on green hydrogen production

Abstract

Techno-economic analysis (TEA) is a tool for analyzing the economic feasibility of a technology. TEAs have increased their importance as companies look to come up with cost-competitive alternatives for emissions-intensive technology solutions. However, TEAs have been found to suffer from a lack of transparency of assumptions, which limits their application in follow-up studies. Lack of knowledge (LoK) is often assumed as one group of unknown things in the system. Thus, to improve the transparency of TEAs, the LoK, that has an impact on the analysis should be analyzed and reported. The LoK is particularly high in the early stages of the technology development, and therefore a more detailed analysis on the LoK might provide interesting perspectives on decision making with regard to new technologies.

The objective of this thesis is to build a TEA of a hydrogen production plant that produces green hydrogen using concentrated photovoltaics (CPV) and anion exchange membrane water electrolysis (AEMWE) technologies. There, a special focus is placed on the different types of LoK within the system; uncertainty, ambiguity, and system-level LoK. Based on the reviewed literature on different types of knowledge, system engineering, technology commercialization, and cost estimation, a framework for a new technology TEA formulation is developed. The framework is applied in the formulation of a TEA for a green hydrogen production plant. The model structure used in TEA is introduced and the values of the input variables and their uncertainty and ambiguity are estimated. Thus, ambiguity and uncertainty in the system are analyzed and quantified.

The study shows that the LoK within a system can be quantified and that uncertainty and ambiguity can be separated from each other. Uncertainty and ambiguity are found to behave differently through the technology development process; ambiguity decreases when the system knowledge increases, but uncertainty remains unchanged. The variables with the greatest contribution to ambiguity and uncertainty can be recognized through sensitivity analysis, which allows addressing the most critical issues with regard to the LoK in the system. The quantification of ambiguity and uncertainty is made through Monte Carlo simulation. As a result of the model, the levelized cost of hydrogen (LCOH) is found to be between 27,87 and 96,35 euros, with ambiguity included, and uncertainty is shown as a probability distribution. The calculated LCOH significantly exceeds the LCOH of gray hydrogen and the LCOH of green hydrogen in other models found in the literature. Thus, more work needs to be done to find ways to reduce the production cost with this system.