- genre: break‑out‑group
- title: Resilience and extreme events in energy system models - best practices for stress tests and datasets
- presenter: @aleks-g, @luk23
- description:
We suggest a break-out group in which we can discuss common approaches and practices to resilience and extreme events. Hopefully we can compile a document that could be useful to the openmod community, which we could share afterwards or upload in the wiki.
We want to go through some fundamentals: how do we define resilience for energy modelling? How do we implement such considerations from a more qualitative, planning perspective and how from a quantitative modelling perspective?
Are there any existing frameworks and open data that can be helpful as guidance for stress tests or scenario generation? How do we study these matters systematically and not just as a collection of all possible scenarios we could come up with?
Lukas and I are happy to give more input on how this can be done in the context of weather and climate resilience and extreme weather. But also here, we need to agree on what falls under this category: natural disasters, infrastructure damage, dunkelflauten, climate change.
What climate and weather data can we use to study and answer such questions? Usually, energy system models use reanalysis data (such as ERA5), but synthetic data, climate models (e.g. as part of CMIP6), expired weather forecasts could increase the number of realisations and thus improve the assessment of risks. Which open tools and packages can we use to study rare, but extreme situations in the energy system?
One objective of this break-out session would be to coordinate and harmonise different approaches that have been used across different open models and exchange insights.
- background: Craig et al, 2022 and McCollum et al, 2020. @luk23 is a PhD student at the Technical University of Denmark. @aleks-g is a postdoc (also at DTU). Both use PyPSA-Eur to investigate the impact of extreme weather and climate change on highly renewable energy systems.