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Record W2755126874 · doi:10.15173/esr.v23i1.3311

On the Impact of Wind Feed-in and Interconnections on Electricity Price in Germany

2017· article· en· W2755126874 on OpenAlexvenueno aff
François Benhmad, Jacques Percebois

Bibliographic record

VenueEnergy Studies Review · 2017
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsSpot contractElectricityVolatility (finance)Electricity marketWind powerEconomicsElectricity priceElectricity generationBusinessMonetary economicsEconometricsPower (physics)Financial economicsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

In this paper, we explore carry out an empirical analysis for Germany, as a country with high penetration of wind energy, to investigate the interaction between the well-known merit-order effect, i.e., falling spot price levels as well as highly fluctuating spot prices and the European electricity grids inteconnections,i.e., market coupling.Our main empirical findings suggest that wind power in-feed decreases electricity spot price level but increases spot prices volatility. Furthermore, the relationship between wind power and spot electricity prices can be strongly impacted by European electricity grids interconnection which behaves like a safety valve lowering volatility and limiting the price decrease. Therefore, the impacts of wind generated electricity on electricity spot markets areless clearly pronounced in interconnected systems

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.684
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.297
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2017
Admission routes1
Has abstractyes

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