MétaCan
Menu
Back to cohort

Grid Support Functions Impact on Residential Voltage Profile for Updated Canadian Interconnection Standard

2019· article· en· W3017566292 on OpenAlexaffabout
Nayeem Ninad, K. E. Abraham, Sanjayan Srikumar, Pavithran Gurunathan, Dave Turcotte

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsOvervoltageInterconnectionAC powerReliability engineeringDistributed generationPower factorGridElectrical engineeringVoltageVoltage optimisationEngineeringComputer scienceRenewable energyTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

The high penetration of distributed energy resources (DERs) (especially PV) presents a number of technical challenges for power system operation; one of them being overvoltage. To better manage the grid operation, the interconnection standards around the world are including requirement of grid support functions (GSFs) for these DERs. The recently updated Canadian interconnection standard, CSA C22.3 No. 9 also included advanced GSFs requirements for these DERs. This paper investigates the impact of high PV penetration on the voltage profile of Canadian suburban residential neighborhood. The initial base case is established with the consideration of the legacy PV inverter (unity power factor operation) in 216 houses in which case voltage violation is observed in the network. Then the voltage profile of the neighborhood is compared for three separate scenarios with different GSFs; fixed power factor, Volt-Var and Volt-Watt. Each GSF is configured according to the CSA C22.3 No. 9 standard. These functions can mitigate/reduce the overvoltage issues in different proportions, e.g., voltage violation does not occur for fixed power factor operation. The impact of these GSFs on the customer PV production (active power) and the loading of the network component are also analyzed in this paper.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.364
Threshold uncertainty score0.996

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)0.0050.000

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 head0.004
GPT teacher head0.203
Teacher spread0.199 · 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 designNot applicable
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

Citations8
Published2019
Admission routes2
Has abstractyes

Explore more

Same topicMicrogrid Control and OptimizationFrench-language works237,207