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Record W2717130246 · doi:10.1109/tpwrs.2017.2718512

Demonstrating Stacked Services of a Battery in a Wind R&D Park

2017· article· en· W2717130246 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Power Systems · 2017
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsWind Energy Institute of Canada
Fundersnot available
KeywordsAutomatic Generation ControlWind powerLimitingWind speedBattery (electricity)Electric power systemEngineeringPower (physics)Electrical engineeringAutomotive engineeringReliability engineeringMeteorologyGeography

Abstract

fetched live from OpenAlex

This paper describes the demonstration and evaluation of stacking wind power time-shifting and regulation by a 1 MW/2 MWh battery energy storage system (BESS) within a 10 MW wind park. The BESS time-shifted 15.8 MWh of wind power to peak periods while responding to the automatic generation control (AGC) signals that provide regulation over the 24 day test period. Its fast response time and accurate output allowed the BESS to provide both services simultaneously. Limiting the charging to periods when wind power was available lowered the amount of time-shifting and AGC that could be provided. Some form of AGC was delivered from the BESS for 78.5% of the test period and, if it were remunerated at the PJM rate when the test was performed, it would have earned 8627 USD, with 97% from regulation and the rest from time-shifting wind power. Using PJM's performance template, the BESS averaged a performance score of 70.5% during hours when regulation was performed. This work adds to the growing empirical data that is informing models of and policy for grid storage.

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)0.000
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 score0.568
Threshold uncertainty score0.529

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)0.0000.000

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 head0.213
Teacher spread0.203 · 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