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Reposted by Felix Schmidt

Emil Dimanchev @emildimanchev.bsky.social · 26/03/2024

Excited to share a new paper! We find that renewable subsidies may cost less than often thought because subsidies can correct a market failure that is often ignored. Same applies to CO2 pricing. Open access: findingspress.org/article/9499...

findingspress.org

Effects of Electricity Sector Climate Policies in a Second-best World of Missing Risk Markets | Published in Findings

By Emil Dimanchev, Stein-Erik Fleten & 2 more. Estimates of climate policy costs are inflated when inefficiencies of financial markets are ignored.

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Felix Schmidt @fsschmidt.bsky.social · 26/01/2024

In the future, we intend to include further refinements like on-demand accuracy and cut generation. The setup can also be extended to abandon the perfect foresight assumption within a year, study long-term dynamics of long-duration storage or to represent endogenous learning. 10/10

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Felix Schmidt @fsschmidt.bsky.social · 26/01/2024

Using stabilization and parallelization, the algorithm scales well with the number of weather years. In our tests, the reference configurations consistently outperform Gurobi from 8 weather years, for some cherry-picked configurations already at 2 weather years. 9/10

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Felix Schmidt @fsschmidt.bsky.social · 26/01/2024

Second, the structure of the decomposed problem allows solving the scenarios in parallel. Some overhead remains but the speed-up usually amounts to half the number of scenarios, e.g. four times faster for eight weather years relative to solving the scenarios sequentially. 8/10

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Felix Schmidt @fsschmidt.bsky.social · 26/01/2024

By robust and implementable, we not only mean the complexity of coding the algorithm but also a low sensitivity to hyperparameter tuning, which can prove quite tricky and have a major effect on performance. 7/10

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Felix Schmidt @fsschmidt.bsky.social · 26/01/2024

First, stabilization limits the step size of the algorithm preventing oscillation. We find that the most robust and implementable approaches for this problem are linear/quadratic trust regions (ex. shown below for 3 dimensions) improving performance by a factor of 10 to 20. 6/10

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Felix Schmidt @fsschmidt.bsky.social · 26/01/2024

Yet, the standard Benders converges slowly, and commercial solvers can still solve the original linear program faster by a factor of 100. Hence, we scoured the convex optimization literature for refinements to speed up the algorithm. I focus on the two most effective ones: 5/10

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Felix Schmidt @fsschmidt.bsky.social · 26/01/2024

We split this linear optimization problem into an expansion part and independent operational parts, one for each weather year to avoid a single unsolvable big problem. Benders decomposition then iteratively solves the individual problems, converging to the optimal solution. 4/10

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Felix Schmidt @fsschmidt.bsky.social · 26/01/2024

The algorithm solves a two-stage stochastic problem. The first stage covers capacity expansion; the second operation for different scenarios representing weather years. The setup includes short- and long-duration storage — critical for systems with high shares of renewables. 3/10

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Felix Schmidt @fsschmidt.bsky.social · 26/01/2024

Our new European Journal of Operational Research paper adopts and compares various refinements to a Benders Decomposition algorithm to find a fast and implementable way of accounting for climate uncertainty by including many weather years. 2/10

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Felix Schmidt @fsschmidt.bsky.social · 26/01/2024

🚨New publication 🚨 How to deal with high inter-annual variation of renewable feed-in in sector-coupled energy planning when including multiple years of data in large-scale models is usually intractable? doi.org/10.1016/j.ej... @anygoeke.bsky.social & Mario Kendziorski

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Reposted by Felix Schmidt

DIW Berlin @diw.de · 01/12/2023

🎧Podcast-Tipp: Seit Dezember 2021 ist die Ampel-Koalition im Amt. Wie sieht die Halbzeitbilanz bei der Energiewende aus? @wpschill.bsky.social & @aroth.bsky.social sehen in einzelnen Bereichen gute Fortschritte, in anderen klaffen große Lücken zwischen Ist- & Sollzustand.

podcasts.apple.com

‎fossilfrei: Der Podcast zum Ampel-Monitor Energiewende des DIW Berlin: #12 Wo steht die Energiewe...

‎Sendung fossilfrei: Der Podcast zum Ampel-Monitor Energiewende des DIW Berlin, Folge #12 Wo steht die Energiewende zur Ampel-Halbzeit? – 1. Dez. 2023

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Reposted by Felix Schmidt

Wolf-Peter Schill @wpschill.bsky.social · 01/12/2023

1/ Halbzeit für die Ampel! Also, falls sie bis zum Ende durchhält. Wie steht es nach zwei Jahren 🚦 um die Energiewende? @aroth.bsky.social, @adelinegueret.bsky.social, @fsschmidt.bsky.social & ich haben aus diesem Anlass ein kleines Special zum Ampel-Monitor Energiewende des @diw.de veröffentlicht.

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Reposted by Felix Schmidt

Wolf-Peter Schill @wpschill.bsky.social · 03/11/2023

1/🚨Update im @diw.de Ampel-Monitor Energiewende: jetzt mit neuen IEA-Daten zur Elektrolyse! Ziel der 🚦 ist eine elektr. Leistung von 10 Gigawatt 2030. Derzeit haben wir erst rund 80 Megawatt in Betrieb - d.h. kaum mehr als zum Ampel-Start, und nicht mal 1% des 2030-Ziels. www.diw.de/de/diw_01.c....

Installierte (elektr.) Leistung von Elektrolyseuren in Deutschland: Stand heute, Ziele und geplante Projekte nach Status

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