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Record W1502573839 · doi:10.1109/apec.2015.7104587

A self-reconfiguration control regarding recovery effect to improve the discharge efficiency in the distributed battery energy storage system

2015· article· en· W1502573839 on OpenAlex
Yong-Yong Cai, Zhiliang Zhang, Yue Zhang, Yan‐Fei Liu

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsOverchargeControl reconfigurationMicrogridEnergy storageComputer scienceBattery (electricity)Reliability (semiconductor)Reliability engineeringDistributed data storeSelf-dischargeComputer data storageDistributed generationVoltageEfficient energy useAutomotive engineeringEmbedded systemEngineeringDistributed computingElectrical engineeringPower (physics)Computer hardwareRenewable energy

Abstract

fetched live from OpenAlex

The battery energy storage system in the MicroGrid tends to be distributed in the future, to solve the voltage sharing and overcharge/overdischarge problem, achieve high compatibility and reliability, etc. Based on the distributed architecture, this paper proposes a self-reconfiguration discharge strategy regarding the battery recovery effect to further enhance the battery performance and discharge efficiency of the battery energy storage system. The specific control strategy and principle analysis is presented in details, and the experimental result has verified the proposed concept.

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 score0.948
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.003
GPT teacher head0.170
Teacher spread0.167 · 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

Quick stats

Citations12
Published2015
Admission routes1
Has abstractyes

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