MétaCan
Menu
Back to cohort

Stability Analysis of the Converter-Interfaced Remote Gas Field Power Generation

2024· article· en· W4407316376 on OpenAlexaff
Wenze Li, Rui Liu, Yunwei Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPower Systems and Renewable Energy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsField (mathematics)Power (physics)Stability (learning theory)Computer scienceElectricity generationElectrical engineeringElectronic engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

In remote gas-fired power generation, back-to-back converters facilitate precise regulation over power output while concurrently improving power quality and generators’ dynamic response. This paper examines the stability of grid-side converters operating in grid-following and grid-forming modes. Through developing small-signal state-space models for the grid-side of the back-to-back converter, its dynamic characteristics under various controls are accurately captured. Eigenvalue analysis is utilized to evaluate the impact of the grid strength and control parameters on the system stability. Analysis results delineate the stability boundaries under grid-following and grid-forming controls, guiding the selection of a proper control strategy that ensures stable operation with diverse short circuit ratios. Moreover, the influence of control bandwidths on converter’s stability is also revealed, emphasizing the importance of tunning control parameters in practical implementations. Finally, real-time simulations of a 2.5 MW back-to-back converter-interfaced gas power generation system are conducted on the OPAL-RT platform to validate the stability analysis under varying operating conditions.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.999

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)0.0030.000

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 head0.019
GPT teacher head0.242
Teacher spread0.224 · 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 teacher head, not a consensus.

Study designBench or experimental
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicPower Systems and Renewable EnergyFrench-language works237,207