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Record W3195345713 · doi:10.24018/ejers.2021.6.5.2497

Dynamic Modelling of a Solar Energy System with Vehicle to Home Option for Newfoundland Conditions

2021· article· en· W3195345713 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEuropean Journal of Engineering and Technology Research · 2021
Typearticle
Languageen
FieldEngineering
TopicElectric Vehicles and Infrastructure
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBattery (electricity)EngineeringMode (computer interface)Automotive engineeringMATLABSoftwareEnergy (signal processing)Photovoltaic systemSimulationElectrical engineeringPower (physics)Computer scienceReal-time computingOperating system

Abstract

fetched live from OpenAlex

This paper discusses the dynamic modelling of a solar energy system with vehicle to home (V2H) option for Newfoundland condition. A location was chosen (13 Polina Road) in St. John’s, Newfoundland, Canada. Using BEopt, Homer and MATLAB software, an optimized system was designed for the chosen site to satisfy the house’s energy demand. Furthermore, the concept of V2H is also implemented with aid of smart current sensors installed in the house. When the power provided by the PV panel and the stored energy in the inhouse battery is less than the load’s energy demand, the Nissan Leaf’s battery used to supply home loads in V2H operation mode. The system operates based on the information generated by the sensors. Detailed system dynamic modelling is also presented along with the simulation results. Eight system control modes are proposed and simulated.

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: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.256

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.226
Teacher spread0.214 · 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