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Record W3037764908 · doi:10.24018/ejece.2020.4.3.213

Design of Renewable Energy System for a House in St. John’s, Canada

2020· article· en· W3037764908 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 Electrical Engineering and Computer Science · 2020
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsRenewable energyZero-energy buildingGridDemand responseEnergy engineeringArchitectural engineeringPopulationComputer scienceProcess (computing)Intermittent energy sourceEnvironmental economicsCivil engineeringEngineeringElectricityElectrical engineeringDistributed generationEconomicsGeography

Abstract

fetched live from OpenAlex

During this period of rising energy demand, utility companies are at a certain point in time, unable to satisfy the overall requirements of their entire consumer population. During this kind of situation, the system, which is, at a micro-scale, can also refer to a zero-energy building, which can also be very prominent in solving this problem. Another thing is that cries of non-renewable energy sources and most of the utility companies are majorly dependent on that kind of energy source, and it keeps along with issues of global warming. A renewable energy-based power system can solve this issue. In this paper, the solution to this problem by introducing the microscale installation of a renewable energy source at the residential level has been presented. For that here, the area selected for this project is located in St. John's, Newfoundland and Labrador, CANADA. Newfoundland is an island; hence, the proposed system would be beneficial here. Building this kind of system is the process of designing, selecting, and calculating the energy demand of equipment and, at last, synchronizing it with the grid to make it as zero energy building. This process depends upon a range of variables, including geographical location, load requirement, and solar irradiation. The required demand, system modeling, simulation, and techno-economic analysis are carried out by BEopt, HOEMR, and MATLAB software.

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: Methods · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score0.257

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.148
Teacher spread0.141 · 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