A Practical Approach for Distribution Transformer Loss of Life Assessment Considering Electric Vehicles Penetration
Bibliographic record
Abstract
The rapid and massive acceptance of electric vehicles (EVs) is causing challenges for distribution transformers (DTs) to operate over their expected lifespan. Unlike substation power transformers, whose life consumed/loss of life (LOL) is monitored by directly measuring winding temperature, the winding temperature of DTs cannot be measured in practice due to their massive population, inexpensive cost, and lack of remote communication. Thus, the LOL of residential DTs are required to be estimated by IEEE Standard C57.91-2011. This work proposes a hardware-free two-stage practical approach to assess the real-time LOL of a distribution transformer in residential premises. The first stage determines the kVA load of a DT, without the need of fixed power factor assumption. The DT kVA load along with the ambient temperature and DT thermal parameters are used for DT LOL assessment. Numerical validation is conducted on real-world data utilizing electricity consumption and ambient temperature of fifteen households in London, Ontario, Canada. The study in this work also includes the penetration of the most popular EVs in Canada, along with the service drop cable data as well as practical secondary distribution circuit configuration.
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 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".