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Record W2153079538

Method for studying and mitigating the effects of wind variability on frequency regulation

2009· article· en· W2153079538 on OpenAlexaff
U.D. Annakkage, David Jacobson, Dharshana Muthumuni

Bibliographic record

Venue2009 CIGRE/IEEE PES Joint Symposium Integration of Wide-Scale Renewable Resources Into the Power Delivery System · 2009
Typearticle
Languageen
FieldEngineering
TopicFrequency Control in Power Systems
Canadian institutionsResearch ManitobaManitoba HydroUniversity of Manitoba
Fundersnot available
KeywordsControl theory (sociology)Automatic frequency controlInertiaWind powerAutomatic Generation ControlTurbineElectric power systemGovernorSystem dynamicsController (irrigation)Representation (politics)Power (physics)Variation (astronomy)EngineeringFrequency responseSensitivity (control systems)Control engineeringComputer scienceControl (management)TelecommunicationsElectronic engineering
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a simulation-based approach to study the effect of wind energy variation on the frequency regulation of a power system. In North America, the quality of frequency regulation is defined in terms of two indices known as Control Performance indices (CPS1 and CPS2). The power system is modelled as a control system with equivalent representation of turbine-governor dynamics. The system inertia is modelled as a single equivalent inertia. The power system external to the system under consideration is modelled as a single equivalent. The model is then used to study the sensitivity of CPS indices to wind variation and the settings of the Automatic Generation Controller parameters. The model also gives the amount of regulation reserves utilized in each simulated scenario.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations9
Published2009
Admission routes1
Has abstractyes

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Same venue2009 CIGRE/IEEE PES Joint Symposium Integration of Wide-Scale Renewable Resources Into the Power Delivery SystemSame topicFrequency Control in Power SystemsFrench-language works237,207