Thread by @euronion42

🚨Study on future options and costs of energy imports for Germany🚨

Our study comparing future options for energy imports to Germany and their costs has finally passed peer-review and is now published.

A thread 🧵

🔑Key findings

- Germany has many options for import
- No one-size-fits-all: Costs strongly depend on what and from where you import
- Costs for renewable alternatives and prices for fossil counterparts converged in last year

(visualisation created with AI b/c it's trendy)

↩ Service: Availability

Study is open-access, available in @PLOSONE :
doi.org/10.1371/journa…

All code and data of course are published as #opensource and #OpenData , see the article for details. @openmod

Together with @Michael_Dueren (@jlugiessen) and @nworbmot (@TUBerlin)

❗Service note

All figures in thread are from paper, CC-BY-4.0, see link above, if not mentioned otherwise.

This is an updated tweet of the earlier (pre-print) version tweeted here:

🚢Challenge

#Germany and #Europe heavily rely on importing #FossilFuels from outside the continent.

This will hardly change, not even with an #EnergyTransition. We’ll keep needing to import energy.

Which energy?
From where?
At what costs?

Fig eurostat: europa.eu/!xvdKqF

🔭Study scope

We look into the future of importing energy carriers produced from renewable energy + CO2 captured from the atmosphere.

We compared imports of 9 energy commodities from 7 countries with the costs for producing them in Germany.

🔭Energy carriers compared:

- #hydrogen (g) and (l)
- #hydrogen carrier by #LOHC
- Synthetic #methane (g) and (l)
- #methanol
- #ammonia
- Fischer-Tropsch fuels (#eFuels , e.g. diesel/gasoline/kerosene)

🪔Resulting LCoE

If you focus on the energy content the range of costs for import is broad:

- H2 (g) by pipeline is cheapest, starting at 36 EUR/MWh
- Fischer-Tropsch fuels is most expensive with costs up to 310 EUR/MWh

Depends on assumptions: WACC (5%,10%) & year 2030 - 2050

🪔Resulting LCoE

If you focus on the energy content the range of costs for import is broad:

- H2 (g) by pipeline is cheapest, starting at 36 EUR/MWh
- Fischer-Tropsch fuels is most expensive with costs up to 310 EUR/MWh

Depends on assumptions: WACC (5%,10%) & year 2030 - 2050

🔎Cost compositions

With a closer look a the costs we can identify cost drivers

1. RES costs for electricity
2. Chemical synthesis
3. Chemical feedstock storage

More flexible syn. processes would reduce costs of 1. + 3.

Electrolysis also contributes, but is of less relevance.

👁️Costs trade-Off (1/2)

Notice trade-off transport vs. synthesis costs in the figure above:

Simple forms (electricity, hydrogen) are cheap to produce but costly to transport.

Complex molecules (e.g. methane, methanol) are expensive to produce but cheap to transport and store.

👁️Costs trade-Off (2/2)

This will be important. Depending on your intended energy use case.

Individuals and society need to ask themselves:

- Do we import for long-term storage?
- Continuous electricity generation?
- Baseload chemical feedstocks?
- Small and easy distribution?

⚗️Chemical feedstocks

Sometimes you want #hydrogen, not #energy.

Levelised Cost of Hydrogen (LCOH) per kg H2 including cracking for indirect H2 imports:

- Best: import hydrogen directly
- non-H2 molecules more expensive
- Methanol becomes competitive with Methane and Ammonia

⚖️Comparison with prices 2022

When we started with the study in 2020, our costs > commodity market prices.

This changed with the energy crisis. Costs and prices now overlap under conservative (Ammonia, Methane) or favourable assumptions (Methanol, Fischer-Tropsch fuels).

⛰️Sensitivities

Results are sensitive to our assumptions.
Lower WACC and RES costs are key determinants of the final costs.

Especially on WACC is something political instruments have a strong leverage on.

📋Supply chain modelling

Each energy supply chain (ESC) individually, islanded, without coupling to other system. Considered major steps for each ESC with costs + energy/material demand.

E.g. for Ammonia by ship

📋More on methods

For all countries:
* land availability analysis
* modelled electricity supply curves for 2030-50
* local electricity demand prioritised

* hourley modelling
* renewables modelled using GlobalEnergyGIS and ERA5 data
* linear capacity invest. optim. using #PyPSA