Analysis of spatial and seasonal distribution of power transmission line thermal aging
Bibliographic record
Abstract
Aging assessment of conductors and other components of electric power networks plays an important role in operation and asset management of power transmission systems. Conductors can lose their tensile strength due to the adverse effects of conductor aging caused by thermal overload, and subsequent annealing. This paper analyses seasonal dependency of the thermal aging using known characteristics of transmission conductor, along with load information and weather data. Weather conditions are derived from historical weather reanalysis and interpolated to locations of the transmission lines. By analyzing the conductor temperatures, aging due to loss of conductor tensile strength is estimated at individual locations along the transmission corridor. This paper is concerned with analysis of spatial distribution of thermal aging along the line for different seasons. The proposed methodology is illustrated using a case study analyzing a power transmission line in interior British Columbia, Canada. The simulation results show strong seasonal dependency of both, thermal aging and transmission capacity. This information is important for transmission network operating procedures, e.g. scheduling of line inspections, maintenance, or reconductoring, and for effective transmission asset management.
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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) | 0.001 | 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".