Regional diversification yields 3-7% for 2 locations and increase with the number of locations (see figure).
For a Germany-wide aggregation, portfolio effects increase to 14-21% (see full paper).

Technological diversification, i.e., a combination of wind and solar, at one location brings the greatest portfolio effects (36% in the exemplary graph).

Temporal matching between H2 production and contracted renewable electricity has been discussed and implemented, e.g., in the context of the EU RED and the US IRA.
Previous studies investigating H2 matching use different assumptions on regional aggregation.
What does that imply?

Recent German survey on accepting onshore wind turbines in residential environment:

Without existing turbines (left), the majority has no or small concerns wrt new projects (27 and 41%)

With existing turbines (right), the majority fully or tendentially support them (44 and 36%)

Dynamic electricity tariffs

In Germany, I often hear that, even with smart meters and dynamic tariff offerings in place, not many consumers would choose them.

Norway is an impressive counterexample: >90% of households are on spot tariffs

Germany keeps falling short of government targets for onshore wind deployment.

But these trends are really promising:

+48% in newly installed capacity
+78% in newly permitted capacity

Quo vadis EU ETS price?

Nice up-to-date synthesis by Pahle et al. from PIK as part of the Ariadne project

https://ariadneprojekt.de/media/2023/12/Ariadne-Documentation_ETSWorkshopBruessel_December2023.pdf

New evidence on "must-run" electricity generation in Germany

When power prices dropped to zero and below for 38 hours in a row at Christmas, 13 GW of controllable generators remained online

(5 bio, 3.4 lignite, 2.8 gas, 1.4 coal, 0.4 oil)

What are the reasons?

In our case study, the estimate flexibility potential with the virtual storage approach is about 6 kWh/EV.

This is 10x smaller than with naive aggregation (which converges to the assumed average battery size of 62 kWh/EV).

The virtual storage approach does not overestimate the solution space in energy terms (i.e. the flexibility potential) because it aggregates the solution spaces of the individual EVs (rather than aggregating constraints).

As an alternative for a (more) accurate representation of EV flexibility, we introduce the virtual storage approach.

This decomposes flexible charging into an inflexible reference charging strategy and a flexible deviation from this reference.

We show that naive aggregation, i.e. adding up individual EV constraints, leads to an overestimation of the fleet's flexibility potential.

Modeling volatility must capture that a fleet of EVs will consume power more smoothly than single EVs.

We show that many diverse profiles are needed to adequately represent the peak load of an EV fleet.

(left axis: per EV, right axis: 15 mn EVs in DE 2030)

Electric vehicles (EVs) have a dark and a light side for the power sector: they may add harmful volatility and provide valuable flexibility.

How can we adequately capture both in energy system models?

Check out our new publication with @jaruschm.bsky.social on this topic below

If disamenity costs were high (which is not clear from the literature), 35% less wind power is built.

Different approaches for linearizing cost-potential curves are tested. The 5-steps-function seems to be a sweet spot.

Energy transition will require substantially *less* mining than the current fossil system

Yes, we need more metals (copper, nickel...) but this increase is overcompensated by a decrease in coal mining

New research at Joule

Free author link: authors.elsevier.com/a/1h%7EXc925...

Planned vs. optimized electrolyzer locations

This is why we need to split the bidding zone (among other reasons)

Comparing new data by EWI Köln (www.eon.com/de/hydrogen/...) with study by Frederik vom Scheidt et al. (www.sciencedirect.com/science/arti...)