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Record W2085646972 · doi:10.1109/pesmg.2013.6672408

Deployment of real-time state estimator and load flow in BC Hydro DMS - challenges and opportunities

2013· article· en· W2085646972 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptimal Power Flow Distribution
Canadian institutionsBC Hydro (Canada)
FundersBC Hydro
KeywordsSoftware deploymentComputer scienceEstimatorState (computer science)SoftwareProcess (computing)Key (lock)Real-time computingReliability (semiconductor)Distribution management systemReliability engineeringPower (physics)EngineeringElectrical engineering

Abstract

fetched live from OpenAlex

The object of this paper is to share experiences on deployment and tuning of real-time advanced applications for distribution and distribution state estimator at BC Hydro control center. During past 4 years, BC Hydro has been engaged in the project to procure Distribution Management System (DMS) with objective to enable real-time power system monitoring and control of distribution network in an optimal manner. The emphasis was placed on advanced network applications such as Volt-Var Optimization that are expected to improve the performance and reliability of distribution network. However, a key application that provides basic inputs to advanced applications is distribution state estimator that calculates power system state of distribution network in the real-time. Deployment of state estimator is a difficult process that relies on a number of prerequisites that include, establishing of distribution network model, calibrating and mapping real-time telemetry, extensive software testing and application tuning.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.430

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 head0.021
GPT teacher head0.214
Teacher spread0.193 · 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

Citations35
Published2013
Admission routes2
Has abstractyes

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