Does Europe need a hydrogen network? 🇪🇺💧🍃⚡️

Not strictly, but it may be cheaper, especially when power transmission reinforcements fail to materialise.

New open-access paper in @Joule_CP with #PyPSA 🪡

📖🔓 https://t.co/janlo9vU7iauthors.elsevier.com/sd/article/S25…
🔎 In this paper with @nworbmot @lisazeyen_lz from @TUBerlin and @martavictoria_p from @AarhusUni we investigated 4 scenarios for a net-zero CO2, sector-coupled European energy system:

- ⚡️with/without power transmission reinforcements
- 💧with/without hydrogen network expansion

New study in @iScience_CP with #PyPSA-Eur combining modelling-to-generate-alternatives (MGA) with global sensitivity analysis (GSA) to show many ways to design cost-effective renewable electricity systems with robustness to uncertain technology costs.

doi.org/10.1016/j.isci…

🧵 This paper with @nworbmot extends a previous study using MGA for renewable electricity system planning.

https://twitter.com/fneum_/status/1308728435787866113?s=20

We added technology cost projections as parametric uncertainty to the structural exploration of near-optimal solutions.

🐍🧑‍🏫💻This semester I taught a new course about Data Science for Energy System Modelling, for which I built a website with energy-focused Python tutorials:

fneum.github.io/data-science-f…

@openmod @protontypes #energytwitter It includes hands-on introductions to various libraries useful for modelling energy systems and processing data: Python, numpy, matplotlib, pandas, geopandas, cartopy, rasterio, atlite, networkx, pyomo, pypsa, plotly, hvplot, and streamlit.

Narrowly following least-cost energy system optimisation results risks inequitable outcomes.

In a paper on near-optimal trade-offs, I show for a renewable European power system that more regionally balanced expansion plans can be achieved at little extra cost below 4% ... ... and that completely autarkic solutions, without power transmission, appear much more costly.

Now published in ESR: doi.org/gjr2fb

Preprint from July 2021: arxiv.org/abs/2007.08379

Providing just a single least-cost solution underplays an immense degree of freedom when planning future energy systems.

There are many near-optimal alternatives with attractive properties like social acceptance due to less onshore wind capacity or limited grid reinforcement. Highlights below, or read full paper at doi.org/10.1016/j.epsr… or last year's preprint arxiv.org/abs/1910.01891.

With @nworbmot @KITKarlsruhe @Helmholtz

Kudos to the pioneers @jfdecarolis and @etrutnevyte!