MétaCan
Menu
Back to cohort
Record W3164527536 · doi:10.24018/ejece.2021.5.2.316

Dynamic Modeling and Simulation of a Stand-alone DC Hybrid Microgrid for a Base Transceiver Station in Nigeria

2021· article· en· W3164527536 on OpenAlexafffund
Cyprian Oton, M. Tariq Iqbal

Bibliographic record

VenueEuropean Journal of Electrical Engineering and Computer Science · 2021
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsMemorial University of Newfoundland
FundersMemorial University of Newfoundland
KeywordsDiesel generatorMicrogridTransient (computer programming)Battery (electricity)Electrical engineeringController (irrigation)Automotive engineeringHybrid powerEngineeringPower (physics)Computer scienceDiesel fuelVoltage

Abstract

fetched live from OpenAlex

This work considers the dynamic modeling and simulation of a DC hybrid power system for a rural base transceiver station in Nigeria currently being powered by an AC diesel generator (DG). The transient behaviour of the system is studied under varying solar irradiation to ascertain the stability of the power supplied to the sensitive telecommunication equipment. Each component of the system is designed and simulated in a MATLAB/Simulink environment and connected to form the whole system. A permanent Magnet DC diesel generator is used as back-up power for the system. A detailed presentation of the solar array, buck converter, battery storage system, battery controller, diesel generator and the load are presented in this paper. The result shows a stable power output to the load at rated voltage of 48 V.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.005
GPT teacher head0.186
Teacher spread0.181 · 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 designSimulation or modeling
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

Citations2
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueEuropean Journal of Electrical Engineering and Computer ScienceSame topicMicrogrid Control and OptimizationFrench-language works237,207