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Record W4321325454 · doi:10.2316/j.2023.203-0464

AN IMPROVED ACTIVE PHASE-SHIFT ISLANDING DETECTION METHOD BASED ON FUZZY ADAPTIVE PID ALGORITHM, 1-6.

2023· article· en· W4321325454 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Power and Energy Systems · 2023
Typearticle
Languageen
FieldEngineering
TopicIslanding Detection in Power Systems
Canadian institutionsnot available
Fundersnot available
KeywordsIslandingPID controllerControl theory (sociology)Fuzzy logicAlgorithmComputer sciencePhase (matter)EngineeringControl engineeringArtificial intelligenceElectrical engineeringControl (management)PhysicsTemperature controlDistributed generation

Abstract

fetched live from OpenAlex

In the process of islanding detection, the traditional positive feedback active frequency shift method takes a long time and affects the power quality.The islanding detection characteristics and detection principle of photovoltaic microgrid are analysed.Combined with the fuzzy adaptive PID detection, the feedback parameters are adjusted according to the frequency deviation and deviation change PCC rate to improve the islanding detection efficiency.A fuzzy adaptive PID control algorithm is used to optimise the feedback coefficient in real time.To meet the requirement that the detection error increases due to the constant change of system load.The algorithm introduces frequency difference feedback to optimise the feedback constant of island detection and improve the speed of island detection.The simulation results show that this method can not only quickly short the detection time but also reduce the blind area and improve the efficiency of islanding detection.

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)0.001
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 score0.982
Threshold uncertainty score0.783

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.010
GPT teacher head0.274
Teacher spread0.264 · 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