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Record W2014503273 · doi:10.1109/pesgm.2012.6344711

Support of Contingency Analysis in BC Hydro bulk transmission system operations

2012· article· en· W2014503273 on OpenAlexaff
R. Kishimoto, Ziwen Yao, Veera Raju Vinnakota

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsBC Hydro (Canada)
Fundersnot available
KeywordsSCADAContingencyElectric power systemLoad SheddingElectric power transmissionTransmission networkEnergy management systemContingency planTransmission systemReliability engineeringSupervisory controlComputer scienceTransmission (telecommunications)EngineeringControl (management)Energy managementPower (physics)Energy (signal processing)TelecommunicationsComputer securityElectrical engineering

Abstract

fetched live from OpenAlex

During the summer 2011, two forced outages occurred on power lines in British Columbia (BC) Hydro system. Market conditions and generation pattern stressed the power network in operations and additional generation shedding was required. Contingency Analysis tool in SCADA (Supervisory Control And Data Acquisition)/EMS (Energy Management System) system was used in order to determine the additional generation shedding and it provided security to the parallel paths to mitigate overload impacts for next contingencies. The purpose of this paper is to share BC Hydro experience during this scenario and how Contingency Analysis in SCADA/EMS system supported the operation.

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)0.001
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.954
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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