Feasibility Studies on the Proposed Developments to Be Added In the Existing Electrical Network by Using ETAP
Bibliographic record
Abstract
This paper reviews the existing 11kV cabling and 11kV switchgear of the given electrical network to assess the present capacity to carry continuous load, and the effect that new developments will consequently have on the existing network's ability to support the additional loads by using ETAP.This paper has been produced to set out the results of a modelling exercise that has been undertaken on one of our client's main 11kV distribution network.Load flow assessment shows that out of 8 proposed developments (PDs), four PDs can be accommodated in the existing network while four PDs cannot be accommodated in the existing network individually.It is found that in this study the existing network in some places is near its capacity, and indeed for some sections of the network the 11kV cabling is likely to overload under certain switching scenarios, especially when the existing's network embedded generation is not operating.This presents the existing network with significant issues when switching the network for maintenance purposes or to isolate a fault.It also demonstrates that this network needs to ensure that its embedded generation has a very high availability.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".