Technical Losses in Non-Rural Distribution Feeders of Nawabshah Substation - Analysis & Estimation
Why this work is in the frame
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Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it