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Record W3158243978

Technical Losses in Non-Rural Distribution Feeders of Nawabshah Substation - Analysis & Estimation

2020· article· en· W3158243978 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectricity Theft Detection Techniques
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsElectric power distributionElectricityEstimationDistribution (mathematics)Environmental scienceEngineeringReliability engineeringElectrical engineeringMathematicsVoltage
DOInot available

Abstract

fetched live from OpenAlex

This paper presents the energy loss of the non-rural distribution feeder. Currently in Pakistan, the distribution companies in Water and Power Development Authorities (WAPDA) have implemented different methods to reduce technical losses of distribution feeders. But these methods are difficult to adopt due to their complexities. Therefore, the main aim of the research is to assess the energy loss of non-rural distribution feeders of Nawabshah region. The methodology is based on an on-site survey while providing the inductive loads on distribution feeders. Three main parameters have been analyzed in this study which include monthly power loss in percentage, power factor (PF), and line capacity. The method adopted for the on-site survey and the results obtained through the analysis of thecollected data unraveled the techniques which lead to a substantial reduction in electricity cost and improvement in the overall efficiency of the system.

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: none
Teacher disagreement score0.644
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.006
GPT teacher head0.227
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

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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