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Record W2133082743 · doi:10.1049/cp:20020069

Assessing the reactive power support requirements for generators in a competitive electricity market

2002· article· en· W2133082743 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptimal Power Flow Distribution
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsElectricity marketElectricityElectricity generationAC powerElectricity retailingComputer sciencePower (physics)Electrical engineeringEngineeringVoltagePhysics

Abstract

fetched live from OpenAlex

Under the new competitive electricity market structure, the active power provided by the generator has become a commodity, entering the transmission grid with few restrictions. It is known that the transmission of active power needs the support of reactive power and the amount of support is a function of the active power transmitted. Our studies found that each generator does need a certain amount of reactive power to support the transmission of its own active power. The amount needed is a function of the generator location, the amount of active power transmitted and others. Any reactive power beyond this amount is purely used as reactive power support and should be remunerated. The main objective of this paper is to present an investigation on the problem of assessing the reactive power support of the generator. In this paper, we propose the concept of minimum VAr requirement (Q/sub min/) for generators. A practical approach to determine the Q/sub min/ has also been developed and tested in a 5-bus system and a medium-sized system. Promising test results verify the validity of the proposed method.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.271
Teacher spread0.247 · 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

Quick stats

Citations2
Published2002
Admission routes1
Has abstractyes

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