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Record W4322756779 · doi:10.5281/zenodo.7691155

Battery Energy Storage Based Frequency Control Scheme for Microgrid

2023· article· en· W4322756779 on OpenAlexaff
Hridi Juberi, Md. Tanvir Ahmed

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldEnergy
TopicPower Systems and Renewable Energy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMicrogridBattery (electricity)Energy storageScheme (mathematics)Automatic frequency controlAutomotive engineeringComputer scienceControl (management)Electrical engineeringEngineeringPower (physics)PhysicsMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

<em>This paper proposes a battery energy storage system (BESS) based frequency controller featuring micro grid with high level penetration of renewable energy resources (RES). The frequency controller gives an indication about some of the features that assists to enhance the stability of main power grid or more specifically micro grid and also overcome any imbalance in frequency occurring from any disturbance or fluctuation in system. The imbalance may occur due to increasing or decreasing of load. System frequency undergoes instable region due to the mismatch between power generation and demand and under this circumstances micro sources slowly respond to overcome this zigzag situation. To solve this situation a controller has been designed that responds to the frequency deviation within a specified limit or defined range which has been calculated by the implementation of trial and error method. After designing the controller, some cases have been observed by varying the system load in various situation. Simulations and experimental results assesses the proposed control solutions.</em>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.003

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 head0.024
GPT teacher head0.224
Teacher spread0.200 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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