MétaCan
Menu
Back to cohort
Record W1989936942 · doi:10.1109/ias.2014.6978500

Considerations in the design of grounding system for solar farms

2014· article· en· W1989936942 on OpenAlexaff
Eduardo H. Enrique, Ibro Hadzismajlovic, Ben Shen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsGroundEarthing systemSoil resistivityRackPhotovoltaic systemEngineeringInverterInterconnectionElectrical engineeringArchitectural engineeringEnvironmental scienceCivil engineeringTelecommunicationsMechanical engineeringVoltage

Abstract

fetched live from OpenAlex

A solar farm can be divided in three distinct areas: the substation, the inverter houses and the solar arrays. The interconnection of the grounding grids of these three areas constitutes an extended grounding system. The characteristics of this grounding system are unique to solar farms. There are different factors affecting the performance of this grounding system such as the electric resistivity of the soil at different locations within the farm, the year round weather conditions, the layout of the solar racks and the design of the rack piles. It is critical to take into account all these factors when designing the grounding system to comply with the requirements specified by the codes and standards. These requirements are the touch potential, the step potential and the ground potential rise. The factors affecting the design of the grounding system in a solar farm are described in this study.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.043
GPT teacher head0.264
Teacher spread0.220 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations4
Published2014
Admission routes1
Has abstractyes

Explore more

Same topicPhotovoltaic System Optimization TechniquesFrench-language works237,207