Enjoy the read and we are looking forward to your questions and feedback π‘
Enjoy the read and we are looking forward to your questions and feedback π‘
3) H2 modelers should make the omission or overestimation of portfolio effects transparent when investigating individual locations or entire regions.
2) H2 policymakers should consider potential discrimination against small H2 producers (without access to diverse portfolios) when regulating temporal matching.
We draw the following conclusions:
1) H2 producers should diversify their renewable generation portfolio under strict temporal matching requirements.
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).
In our new working paper, we show that if (and only if) temporal matching is required, market participants with more diverse portfolios can produce green hydrogen more cheaply than those with less diverse portfolios.
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?
New Working Paper:
Portfolio Effects in Green Hydrogen Production Under Temporal Matching Requirements
By Nieves Casas, Reinhard Madlener, and me
Link to full paper: papers.ssrn.com/sol3/papers....
Short summary below π
You were right, @plehmann.bsky.social, the plot in my earlier post was wrong. Here is the right one. Thank you for making me aware :)
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%)
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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
Interested in externalities of renewable energy?
Check out this (mostly open-access) special issue in Environmental and Resource Economics @SpringerEnviro, edited by @plehmann.bsky.social and Brett Day, to which we had the honor to contribute:
link.springer.com/journal/1064...
Source: https://www.fachagentur-windenergie.de/veroeffentlichungen/ausbauentwicklung/
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
13 GW is much less than some very old studies I know:
- Nicolosi 2012 observed DE power prices dropping below zero at 20-30 GW
- FGH et al. 2012 found that 25 GW are needed for system security
Has someone seen more recent analyses on this topic?
High start-up costs may prevent plants from ramping down, but unlikely for 38h in a row, I think.
Other reasons for must-run:
1) Grid services: balancing & redispatch
2) Combined heat and power (CHP)
3) Ill-designed support schemes (for biomass and CHP)
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?
Deadline: 12-Feb-2024
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15-Mar-2024
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The new year begins with a series of conference submission deadlines ππ
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Here is the link to the (open-access) article: www.sciencedirect.com/science/arti...