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Record W2532155703 · doi:10.1109/ipec.2005.207046

Reliability component in transmission service pricing

2005· article· en· W2532155703 on OpenAlexaboutno aff
Wenyuan Li, Jiping Lu, Wei Yan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsWheelingComponent (thermodynamics)Reliability (semiconductor)Reliability engineeringTransmission systemComputer scienceTransmission (telecommunications)IncentiveService (business)Investment (military)EngineeringTelecommunicationsBusinessEconomicsPower (physics)Microeconomics

Abstract

fetched live from OpenAlex

This paper presents a method to develop and incorporate a reliability component in transmission pricing. The method includes the following three tasks: developing a technique to establish an unit reliability value; quantifying impacts of customer on system reliability; and incorporating the reliability component in the rate design. The proposed method calculates the charge or credit to a native, wheeling, or generation customer in terms of its impact on system reliability. Incorporation of the reliability component will force all players in the system (the utility and customers) to share their responsibility in system reliability through a price signal and provide an incentive message to encourage the right siting of new generations. The method also reflects the long run incremental investment requirement of a transmission company. The procedure of the proposed method has been explained using the BC Hydro system in Canada as an example

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)0.004
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.005
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.002

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 head0.005
GPT teacher head0.193
Teacher spread0.188 · 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 designTheoretical or conceptual
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

Citations3
Published2005
Admission routes1
Has abstractyes

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