Thrust 4 – Technoeconomic Analysis

Project 4.1 – Technoeconomic Analysis (Matthew Stuber)

Background: A crucially important step in the commercialization of new technology is a technoeconomic analysis.  Further, certifying new technologies as sustainable requires a lifecycle analysis.  The concept of the H2 economy is not new, yet as scientific pursuits aim to enable various aspects of it, they often do so in a vacuum and fail to consider technoeconomic feasibility and/or environmental impact. The National Renewable Energy Laboratory (NREL) has created digital tools for the technoeconomic analysis of integrating renewable energy (SAM) as well as H2 analysis tools (H2A, H2FAST), including life cycle.  Although such tools are quite sophisticated, they lack easy integration with rigorous mathematical optimization tools and general user-defined mechanistic models.

Objectives: In this task, REU students will work closely with those assigned to the other projects to develop economic models for the various H2 technologies discussed above.  Both early-stage and later-stage technologies will be considered. When possible, these models will be granular enough to account for individual process technologies and unit operations and functionalized by scale and inputs/outputs. Formal analyses will be conducted using these models, those in SAM, H2A, and H2FAST, and mathematical optimization to determine the potential value propositions.  In addition, lifecycle analyses will be conducted to assess the overall environmental impact of the various technologies. Students will first learn the fundamentals of technoeconomic analyses and lifecycle analyses, as they are currently applied.  Then, students will develop and implement mathematical models in the Julia programming language and the JuMP algebraic modeling language for mathematical optimization. Students will then be exposed to introductory mathematical optimization theory and practice and will learn to develop value propositions for the various solutions through potential business models.

Expected Outcomes: By the end of this task, students will be able to implement and use mathematical models and mathematical optimization for technoeconomic analysis and lifecycle analysis and determine value propositions with competitive business models.