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Record W2752437910

Influence of Renewable Energy Sources on Electricity Transmission Networks in Central Europe

2017· preprint· en· W2752437910 on OpenAlexfundno aff
Karel Janda, Jan Málek, Lukáš Rečka

Bibliographic record

VenueEconstor (Econstor) · 2017
Typepreprint
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsnot available
FundersMcGill UniversityGrantová Agentura České RepublikyEuropean CommissionUniverzita Karlova v Praze
KeywordsRenewable energyVolatility (finance)ElectricityWind powerSolar powerEnvironmental scienceGrid parityElectricity systemElectric power transmissionEnvironmental economicsEconomicsNatural resource economicsElectricity generationMeteorologyBusinessEngineeringEconometricsPower (physics)Electrical engineeringDistributed generationGeographyPhysics
DOInot available

Abstract

fetched live from OpenAlex

This paper focuses on the influence of increased wind and solar power production on the transmission networks in Central Europe. The model ELMOD is employed. Two development scenarios for the year 2025 are evaluated on the basis of four representative weeks. The first scenario focuses on the effect of Energiewende on the transmission networks, the second one drops out nuclear phase-out and thus assesses isolated effect of increased feed-in. The results indicate that higher feed-in of solar and wind power increases the exchange balance and total transport of electricity between transmission system operator areas as well as the average load of lines and volatility of flows. Solar power is identified as a key contributor to the volatility increase, wind power is identified as a key loop-flow contributor. Eventually, it is concluded that German nuclear phase-out does not significantly exacerbate mentioned problems.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.194
Teacher spread0.187 · 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.

Study designSimulation or modeling
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

Citations1
Published2017
Admission routes1
Has abstractyes

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