Assessment of high voltage auto-transformer spare requirements in bulk transmission systems
Bibliographic record
Abstract
High voltage auto-transformers represent an important component of bulk transmission systems and are used to transform voltage from one level to another. These auto-transformers are critical for regional load supply, inter-regional load transfers and for certain generator/load connections. Major or catastrophic failures to this equipment can have severe consequences to electric utilities in terms of increased operating costs and customer load losses. To minimize the impact of this type of failures, utilities may carry some spare units to guard against such events. These spare units are going to cost utilities money (utility cost) to purchase, to store and to maintain and utilities should try to strike the right balance between the utility cost and the risk cost (if spare units are not there). This paper describes a probabilistic approach for assessing the risk associated with catastrophic failures of auto-transformers used in bulk transmission systems with and without availability of spare units. The computed risk will be expressed in dollars and will be added to the cost of carrying any spare units. The required number of spare units (optimal) is obtained when the total cost, utility and risk costs, is minimal. Sensitivity studies are carried out to determine the system parameters that have dominant impacts on the optimal number of spares. An example is presented to illustrate the proposed assessment methodology.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".