Techno-Economic Assumptions: From Silos to Synergies
Format: Workshop (group discussions + short presentation + hands-on)
Organiser: Johannes HAMPP
Preferred duration: 3h
Description: Getting the right assumptions on technologies into a model is complex and time-consuming. While AI-based tools can accelerate the processing of large quantities of sources, we still need to understand the content, technology system boundaries, and properties to properly represent and integrate technologies into our models.
In this do-a-thon, we’ll work in groups to collect and share experiences on how you handle techno-economic assumptions: how you research them, how you record them, and what best practices (or pain points) you’ve found along the way. If you’d like to give a short show-case of your own approach, reach out to me beforehand to arrange it. We’ll collect and summarise the group insights together.
I’ll also give a short introduction to a our prototype Python library for techno-economic analysis and assumption-integration into energy system models (covering things like currency conversion, inflation adjustment, learning curves, and growth models), followed by hands-on time to try it out, give feedback, and help shape further development.
Technology data management has for too long been done in silos and on a project-by-project ad-hoc basis, hurting quality and wasting effort on something that should take much less time. Let’s change that together.
Background: For a few years, we’ve maintained a repository of techno-economic assumptions for a range of technologies, which has grown beyond the PyPSA community and attracted outside users. This session builds on that work, aiming to move from “good-enough starting assumptions” to a more robust, shared, well-documented approach. Combining better documentation and learning materials, with the right tools and data formats to enable collaborative reuse and sharing of techno-economic data for energy system models.
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