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Novel Control of Battery Energy Storage System (BESS) as STATCOM (BESS-STATCOM) for Stabilization of a Critical Motor

2023· article· en· W4387951325 on OpenAlexaffabout
Rajiv K. Varma, Milad Ahmadi, Cristian Arpino

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsWestern University
Fundersnot available
KeywordsInduction motorControl theory (sociology)Battery (electricity)InverterEngineeringPower (physics)InstallationEnergy storageComputer scienceControl (management)Control engineeringAutomotive engineeringVoltageElectrical engineering

Abstract

fetched live from OpenAlex

A new control for operating a Battery Energy Storage System (BESS) as a STATCOM, termed BESS-STATCOM, is proposed to stabilize a critical induction motor against large disturbances on a 24/7 basis to prevent significant financial losses to the motor facility. Simulation studies are performed using PSCAD on the realistic distribution feeder with a BESS to demonstrate the effectiveness of the proposed control method. When a large disturbance is created, even if the BESS is in a high state of charge or discharging, the control system curtails the active power to release the entire inverter capacity for operating as a STATCOM. This active power curtailment lasts for less than a minute. During this time, the induction motor is stabilized. The proposed BESS-STATCOM technology is expected to be ten times more economical than installing a new STATCOM of equivalent size for stabilizing the same critical motor. The proposed BESS-STATCOM control will soon be field demonstrated in the utility network of Elexicon Energy, Ajax, Ontario.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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 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

Citations7
Published2023
Admission routes2
Has abstractyes

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