Technoeconomic Modeling of Carbon-Removal/Decarbonization Technologies

[Grigory Bronevetsky]

Modeling Talks

Technoeconomic Modeling of Carbon-Removal/Decarbonization Technologies Corinne Scown, Lawrence Berkeley Tyler Huntington, JBEI Tuesday, Feb 27 | 9am PT Meet | Youtube Stream Hi all, The presentation will be via Meet and all questions will be addressed there. If you cannot attend live, the event will be recorded and can be found afterward at https://sites.google.com/modelingtalks.org/entry/technoeconomic-modeling-of-carbon-removaldecarbonization-technologies Abstract: Systems analysis can put the wide array of emerging decarbonization and carbon dioxide removal (CDR) technologies into context and elucidate some of the tradeoffs they will face at scale. This presentation will explore some of the cost considerations associated with selected CDR technologies, bioenergy, and energy storage. The team will also demonstrate some of the tools they have developed to help researchers, startups, and investors understand the relationship between performance parameters in complex renewable energy production systems and their system-wide costs and impacts. Bios: Corinne Scown is a staff Scientist in the Energy Analysis and Environmental Impacts (EAEI) Division at LBNL, Vice President and founder of the Life-cycle, Economics, and Agronomy Division (LEAD) at the Joint BioEnergy Institute (JBEI), and Head of Sustainability at the Energy and Biosciences Institute (EBI). She is also currently on detail as a senior advisor on clean fuels to the U.S. Department of Energy. Scown’s expertise includes life-cycle assessment, technoeconomic analysis, biofuels and bioproducts, air quality impacts of vehicle electrification, strategies for atmospheric carbon removal, and co-management of energy and water. She leads the development of online tools for TEA, LCA, and bio-based feedstock assessment, including BioC2G and the Biositing tool. Scown was awarded the ACS Sustainable Chemistry & Engineering Lectureship in 2022 for her work on TEA and LCA of emerging technologies and recently served as a member of the NASEM Committee on Current Methods for Life Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Scown earned a B.S. in civil engineering with a double-major in engineering and public policy at Carnegie Mellon University, and she received her Ph.D. and M.S. in civil and environmental engineering at UC Berkeley. Tyler Huntington is a software developer in the Life-cycle, Economics, and Agronomy Division (LEAD) at the Joint BioEnergy Institute (JBEI). He specializes in the development of web-based software for techno-economic analysis (TEA), life-cycle assessment (LCA), and geospatial analysis of bioeconomy resources and infrastructure. A suite of these tools can be found at lead.jbei.org. In addition to his software development work, Tyler has also led several published studies focusing on machine learning methods in the predicting of bioenergy crop yields under future climate scenarios and building surrogate models for proxying biochemical process simulations. Prior to joining JBEI, Tyler earned his bachelor's degree in biology from Swarthmore College in 2018 where he graduated as a Lang Opportunity Scholar in recognition for his work as an undergraduate to promote sustainable agriculture and food justice in the surrounding community. While at Swarthmore, he also performed research on the effects of deforestation on ecosystem services in Brazil in Dr. Elizabeth Nichols' Biodiversity and Environmental Sustainability lab. More information on previous and future talks: https://sites.google.com/modelingtalks.org/entry/home

[Grigory Bronevetsky]

Video Recording: https://youtu.be/CIQ4GNL1bEo

Slides: https://drive.google.com/file/d/1LuPJoN4Q0QgWH18_JAtfGgqNwxGb0umI/view?usp=sharing

Summary:

• Focus: Techno-economic analysis (TEA) and Life-cycle assessment (LCA)

• Past models: 

  • Mostly black-box with hard-to-find data on technological attributes

  • Hard to model costs because technological details are unavailable

• Status Quo:

  • Very detailed models of the technologies

  • Enables

    • Cost/functionality analysis

    • Evaluation of alternative designs 

  • Berkeley Lab: leader in modeling emerging technologies

    • Technology details

    • Location details

    • Transport/operation costs

    • Lifetime energy/water/land/air use/emissions

    • Work across many stages of development: 

      • Early lab/bench experiment

      • Proof of concept/pilot

      • Commercialization

      • Maturity

• Function of TEA/LCA

  • Answering research questions

  • Providing tech-specific insights

  • Comparing/evaluating technologies

  • Developing large-scale scenarios

  • Policy design/regulatory impact assessment

• Sustainable aviation fuels (SAF)

  • Bioeconomy outputs: fuels, plastics, solvents, food, pharmaceuticals

  • Valley of death:

    • Lots of resources available for basic research for new tech

    • Lots of resources for commercialization of proven technologies

    • Few resources for fine-tuning of research outputs to early commercial scale

  • Venture investors have a hard time identifying good investments in diverse early tech field

  • Approach: develop easy-to-use design/cost tools for analyzing these technologies

    • https://lead.jbei.org/tea_lca_tool

    • Used by analysts and investors

    • Identify low-hanging fruit, plan for the long-term

      • Bio-based processes with concentrated CO2 stream (e.g. ethanol production)

      • Value-added products in plants (can predict the concentration of a chemical in a plant that is profitable)

    • Combination of many different models to capture feedstock availability (e.g. DAYCENT)

    • Focus on energy-dense molecules for plane biofuels

• Batteries in Vehicles & the Grid

  • Critical for making renewable energy generation functional (generate at one time, use at another time)

  • Evaluate emissions, pollution, etc.

  • Use of batteries increases costs

  • Cost-effective if we consider all the payments power generators get from utilities for power, availability for discharging on demand (like peaker plants)

  • Integration of many TEA models for a complete view:

    • Heavy-duty truck flows

    • Truck technology

    • Electricity Grid (grid scenarios from NREL)

    • Direct truck emissions

    • Climate and human health -> regional/global impacts

  • Evaluated impact of freight electrification over time

    • From perspective of climate, electrification is very effective even when clean power cost is high

    • From perspective of human health it takes longer for benefits to be seen

    • Public policy can make electrification much more cost effective (can accelerate decarbonization by a decade)

  • Crucial to select the appropriate battery chemistry

    • Actively working on modeling battery performance and lifetime

• Carbon dioxide removal (in slides)