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Record W1972238552 · doi:10.1109/isgt.2012.6175758

PEV-based combined frequency and voltage regulation for smart grid

2012· article· en· W1972238552 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
TopicElectric Vehicles and Infrastructure
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSmart gridPlug-inComputer scienceGridPopularitySet (abstract data type)VoltageVoltage regulationFrequency regulationAC powerAutomatic frequency controlPower flowDynamic pricingOperations researchElectric power systemPower (physics)TelecommunicationsEngineeringElectrical engineeringEconomicsMicroeconomics

Abstract

fetched live from OpenAlex

With the increasing popularity of plug-in electric vehicles (PEVs), they will be able to help the power grid by providing various ancillary services. In fact, recent studies have suggested that PEVs can participate in frequency regulation. In this paper, we consider offering both, i.e., combined, frequency and voltage regulation by PEVs. In this regard, we first investigate a set of constraints that need to be taken into account on PEVs' active and reactive power flow to offer ancillary services. Next, we formulate two joint optimization problems, based on different pricing and contract scenarios, that can be solved for optimal combined offering of frequency and voltage regulation by PEVs. They address both day-ahead command-based and day-ahead price-based models. Simulation results show that the proposed designs can benefit both users and utilities.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.256

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)0.0000.000

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 head0.006
GPT teacher head0.189
Teacher spread0.183 · 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

Citations72
Published2012
Admission routes1
Has abstractyes

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