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Record W3134416216 · doi:10.1109/icjece.2020.3034265

A New Energy Storage System Configuration to Extend Li-Ion Battery Lifetime for a Household

2021· article· en· W3134416216 on OpenAlexafffundvenue
Mehdi Alimardani, Mehdi Narimani

Bibliographic record

VenueCanadian Journal of Electrical and Computer Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaMcMaster University
KeywordsBattery (electricity)Energy storageEnergy (signal processing)Electrical engineeringLithium (medication)Power (physics)ElectricityComputer scienceAutomotive engineeringMaterials scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

A new home energy storage system (HESS) configuration using lithium-ion batteries is proposed in this article. The proposed configuration improves the lifetime of the energy storage devices. The batteries in this system can be charged by either using solar panels when solar energy is available or by using the grid power when the electricity cost is at its lowest rate during off-peak hours. In the proposed configuration, the battery bank is split into two sections, and the pulsed charge-discharge method is employed. This method helps to prolong the life of the lithium-ion batteries while maximizing the solar energy utilization that leads to reduce the consumer's total energy cost. In order to demonstrate the benefits of the proposed method, different modes of operation are discussed in detail along with the simulation results. A prototype was developed to demonstrate the performance of the proposed system experimentally.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.004
GPT teacher head0.142
Teacher spread0.139 · 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

Citations14
Published2021
Admission routes3
Has abstractyes

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