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Record W1981217786 · doi:10.3138/infor.48.4.267

On European Electricity Market Liberalization: A Game-Theoretic Approach

2010· article· en· W1981217786 on OpenAlexvenueno aff
Kateřina Staňková, Geert Jan Olsder, Bart De Schutter

Bibliographic record

VenueINFOR Information Systems and Operational Research · 2010
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsElectricity marketLiberalizationElectricityStackelberg competitionProfit (economics)Electricity retailingEconomicsIndustrial organizationPerfect competitionMicroeconomicsBusinessMarket economyEngineering

Abstract

fetched live from OpenAlex

In this paper, we deal with the European electricity market liberalization problem, formulated as a game with electricity producers as players, while the consumers' electricity demand is exogenous. The producers maximize their profit by choosing how much electricity they will produce individually by means of electricity production available to them. The aim of the research presented in this paper is to investigate the differences between the resulting electricity prices with different scenarios: a market with one Stackelberg leading producer, a market with two Stackelberg leading producers being noncooperative among themselves, and a perfectly competitive market. In the case studies the games involving one, two, and eight European countries are played. In the scenarios dealt with in this paper the perfectly competitive market yields the lowest electricity prices for the consumers. However, we also discuss possible drawbacks of liberalization. Our research aims to help understanding the complex process of electricity market liberalization.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
GPT teacher head0.256
Teacher spread0.241 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2010
Admission routes1
Has abstractyes

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