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Record W3195795842 · doi:10.1109/tpwrs.2021.3096953

A Linearized AC Planning Model for Generations and SFCLs Incorporating Transient Stability and Short-Circuit Constraints

2021· article· en· W3195795842 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

VenueIEEE Transactions on Power Systems · 2021
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTransient (computer programming)Resistive touchscreenControl theory (sociology)LinearizationBilinear interpolationNonlinear systemComputer scienceStability (learning theory)Limit (mathematics)Mathematical optimizationMathematicsPhysics

Abstract

fetched live from OpenAlex

Generation expansion planning (GEP) can be a challenging problem when short-circuit (SC) levels and transient stability constraints are considered. We propose a multi-period GEP model in which resistive superconducting fault current limiters (SFCLs) are deployed to limit SC levels, which may be elevated by new generators, and to enhance transient stability at the same time. Through investigating the effect of SFCLs on transient stability and SC levels, efficient linear regions of SFCL deployment are identified and employed to achieve a more cost-effective solution and enhance problem tractability. An effective solution method is also presented by decomposing the main problem into smaller ones. We also propose a linearized AC network framework incorporating bilinear terms based on McCormick envelopes. Relaxation errors are minimized by an exactness loop until the linearized model solution sufficiently matches the original nonlinear model solution. The methodology is illustrated and discussed using the IEEE 118-bus test system.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.887
Threshold uncertainty score0.857

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 head0.049
GPT teacher head0.252
Teacher spread0.204 · 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