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Record W1971280324 · doi:10.1049/ip-gtd:20050438

Locational balance service auction market for transmission congestion management

2006· article· en· W1971280324 on OpenAlexaff
Ramadan El‐Shatshat, Kankar Bhattacharya

Bibliographic record

VenueIEE Proceedings - Generation Transmission and Distribution · 2006
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCongestion managementProcurementBalance (ability)BusinessElectricity marketEnergy marketTransmission (telecommunications)Service (business)Common value auctionIndustrial organizationConsumption (sociology)MicroeconomicsElectricityComputer scienceTelecommunicationsMarketingEconomicsEngineeringElectric power system

Abstract

fetched live from OpenAlex

A novel market design is proposed and developed that uses the energy-balance services for transmission-congestion relief. In this proposed market, all generators and customers have the ability to submit their offers to increase/decrease their generation/consumption, respectively. Each participant provides a ‘price–quantity’ offer to the independent system operator (ISO) which is independent of the energy market and is activated after the energy market is settled. The ISO arrives at the optimal procurement of the balancing services for congestion management based on the ‘importance’ of each market participant to transmission congestion relief using the concept of ‘line specific’ generalised generation-distribution factors.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.006
GPT teacher head0.190
Teacher spread0.184 · 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

Citations8
Published2006
Admission routes1
Has abstractyes

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