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Record W2151888366 · doi:10.1109/ccece.1999.804885

Reliability-based impact analysis of independent power producers for power system operations under deregulation

2003· article· en· W2151888366 on OpenAlexaff
Kenji Okada, Hiroshi Asano, R. Yokoyama, T. Niimura

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsReliability engineeringReliability (semiconductor)Electric power systemDeregulationElectricityPower (physics)Computer scienceConstraint (computer-aided design)Transmission systemElectricity generationMains electricityElectricity marketElectric power industryPower transmissionElectric power transmissionTransmission (telecommunications)EngineeringEconomicsTelecommunicationsElectrical engineering

Abstract

fetched live from OpenAlex

In this paper, the authors present an evaluation procedure of independent power producers' impact on reliability and associated costs of existing power systems under deregulation. Independent power producers (IPPs) with competitive electricity prices can contribute to the cost reduction of electricity supply under the open access power systems. However, there is a concern that the high standard of power system reliability may not be maintained because of possible failures of such new generators. IPPs' effects on supply reliability are closely related to generation and transmission operation of existing power systems. In the proposed approach, the reliability is measured by expected unserved power (EUP) and the additional cost of reliability maintenance is calculated by the cost of generation adjustment. The optimal redispatch problem is solved with the reliability index as a constraint. Also, a transmission system congestion is considered in the redispatch. Numerical simulations have been conducted on a model system with six nodes and seven branches.

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)0.008
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.238
Teacher spread0.230 · 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

Citations17
Published2003
Admission routes1
Has abstractyes

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