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Record W1999266912 · doi:10.1109/tia.2013.2262031

Active Stabilization of DC Microgrids Without Remote Sensors for More Electric Aircraft

2013· article· en· W1999266912 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 Industry Applications · 2013
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMicrogridCapacitorVoltageObserver (physics)CapacitanceInductorComputer scienceControl theory (sociology)EngineeringElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

DC microgrids are increasingly used in transportation systems such as more electric aircraft. Such applications require small and light systems, and thus, the optimization of passive elements like dc-bus capacitor and filtering inductor is an important issue. It is known that the reduction of dc-bus capacitance may lead to instability of the dc microgrid when tightly controlled loads are employed. To overcome this risk, a seductive solution is to implement a centralized stabilization system in the dc microgrid. Nevertheless, a centralized stabilizer requires a lot of sensors and particularly those providing the load input voltages. The latter is often far from the stabilizer, and fast data transmission lines must be provided. In this paper, an observer is developed for estimating the load input voltages, thus removing the required voltage sensors. Its convergence as well as the stability of the whole system is proved. The validity of the proposed method is confirmed by simulations and experimentations.

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 score0.937
Threshold uncertainty score0.847

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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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