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Record W4296053299 · doi:10.1049/pbpo217e_ch5

Detailed modeling of inverter-based resources

2022· book-chapter· en· W4296053299 on OpenAlexaff
Younes Seyedi, Ulas Karaagac, Jean Mahseredjian, Aboutaleb Haddadi, Keijo Jacobs, Houshang Karimi

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTransient (computer programming)EmtpConvertersComputer scienceInverterFault (geology)Control engineeringController (irrigation)Electric power systemPower (physics)Variety (cybernetics)EngineeringReliability engineeringControl theory (sociology)VoltageControl (management)Electrical engineering

Abstract

fetched live from OpenAlex

WPs consist of a large variety of interconnected components including mechanical parts, power electronic devices, control and protection systems, etc. Accurate and generic models for different types of WTs are crucial for reliable design and planning of modern power systems that incorporate WPs. This chapter introduces an effective approach towards detailed modeling and simulation of WPs that employ variable speed WTs. Specifically, converters and their control schemes for DFIG and FSC WTs are thoroughly discussed, and their main parameters are explained. Moreover, software implementation, average value and detailed models, and controller design are addressed. EMTP® is used to verify the accuracy of the generic models under different test cases. Time-domain simulation results are analyzed and compared with the real-life measurements of post-fault transients in the test scenarios. The results confirm that the developed models in conjunction with the EMT simulations can accurately predict the response of DFIG and FSC WTs under both steady-state and transient 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.852
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

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 head0.025
GPT teacher head0.189
Teacher spread0.165 · 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 designSimulation or modeling
Domainnot available
GenreOther

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

Citations4
Published2022
Admission routes1
Has abstractyes

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