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Record W4412082226 · doi:10.1109/tpwrs.2025.3586542

Two-Stage Resilience-Oriented Unit Commitment of Transmission Systems Against Severe Windstorms

2025· article· en· W4412082226 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

VenueIEEE Transactions on Power Systems · 2025
Typearticle
Languageen
FieldEngineering
TopicOptimal Power Flow Distribution
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPower system simulationResilience (materials science)Stage (stratigraphy)Unit (ring theory)Psychological resilienceTransmission (telecommunications)Electric power systemComputer scienceEnvironmental sciencePower (physics)GeologyPsychologyPhysicsTelecommunicationsSocial psychology

Abstract

fetched live from OpenAlex

This paper presents a two-stage unit commitment (UC) model to boost the resilient operational planning of transmission systems against upcoming windstorms. UC scheduling, load curtailment, and repair crew dispatch (RCD) are coordinated in two stages to inform all phases of the resilience trapezoid. Transmission line failure probabilities are calculated using the forecasted wind and component fragility curves. In the first stage, a conservativeness-controlled info-gap (CCIG)-based model is proposed to provide cost-robustness tradeoffs for decision-makers by solving the resilient UC (RUC) problem. Given the realized first-stage decisions, a novel UC-integrated RCD (UCRCD) formulation is presented in the second stage, which employs repair crew teams (RCTs) to minimize load curtailment by scheduling the repair of damaged lines during the UC horizon. The model is further developed to incorporate the RCD rescheduling on a rolling-horizon basis as the event progresses through the system and the damage information is updated. The proposed model is tested on the modified IEEE RTS-79 and IEEE RTS-96 test systems, showing its efficacy in providing optimal cost-robustness tradeoffs for mildly, moderately, and seriously conservative decision-makers and updating restoration schemes according to the new damage information. The results are verified using a sequential Monte Carlo (MC) simulation with 2000 scenarios.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.236
Teacher spread0.227 · 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