Distribution Transformer Remaining Useful Life Estimation Considering Electric Vehicle Penetration
Why this work is in the frame
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Bibliographic record
Abstract
A major portion of a power system's asset portfolio comprises distribution transformers on residential premises. The rapid and massive acceptance of electric vehicles is posing challenges for distribution transformers to operate over their expected lifespan. This work proposes a four-layer framework to assess the real-time and anticipated aging of a distribution transformer and estimate the remaining useful life of a distribution transformer. The first layer stores residential smart meter data to be utilized for the kVA load estimation of a distribution transformer in the second layer. The performance of two powerful forecasting tools, i.e., Time Series Decomposition and Hidden Markov Model, is compared in the third layer. The historical and forecast data, along with the distribution transformer's thermal parameters, are used for its remaining useful life assessment. Numerical validation is conducted on real-world data utilizing electricity consumption and ambient temperature of fifteen households in London, Ontario, Canada. This work also includes the penetration of the most popular electric vehicles in Canada, along with service drop cable data and practical secondary distribution circuit configuration.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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