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Record W4402123817 · doi:10.1109/icjece.2024.3439867

Green Electricity Share Enhancement Through Rooftop Solar PV System on Institutional Sheds

2024· article· en· W4402123817 on OpenAlexvenueno aff
Kola Leleedhar Rao

Bibliographic record

VenueCanadian Journal of Electrical and Computer Engineering · 2024
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPartition (number theory)Environmental scienceForestryGeographyMathematicsCombinatorics

Abstract

fetched live from OpenAlex

Different cases have been exercised to create real-time feasibility for erecting solar photovoltaic (PV) system on the roofs of the seven sheds being utilized as six workshops (WSs) and one central store (CS) within a higher educational institution. The obtained results are so intensive that for the WS and CS sheds, the average daily normalized production (ADNP) in kWh/kWp/Day is more on the south-facing roofs (4.20) followed by west- (4.06), east- (3.96), and north-facing roofs (3.78). The mean average additional energy (MAAE) of about 11.27% and 2.52% can be generated on south- and west-facing roofs compared to the north- and east-facing roofs, respectively. In comparison to the vertical installation (VI), the average specific production (ASP) in kWh/kWp/Annum is more with the horizontal installation (HI) of PV modules on either side of the exposed roofs for WS (1459.25) and less for CS (1454.5). The total maximum energy that can be generated on the roofs of total seven sheds is about 969 566 kWh/Annum, which may reduce about 824.12 ton of CO2 emissions per annum. It is an appreciable figure and could pave a path for establishing green electricity. The outcomes of the presented study address the energy sustainability challenges of a higher educational institution.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.604

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 head0.009
GPT teacher head0.193
Teacher spread0.184 · 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 teacher head, 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Electrical and Computer EngineeringSame topicPhotovoltaic System Optimization TechniquesFrench-language works237,207