Risk assessment of rural diesel generation stations
Bibliographic record
Abstract
The effect of aging assets on reliability has become an important area of study for BC hydro non-integrated area (NIA), due to the fact that many of the assets are approaching the age of retirement. System reliability assessment methods that incorporate the increasing probability of end-of-life failures for these assets are required. This paper outlines one risk assessment method for diesel generation stations based on RISK/spl I.bar/A, a probabilistic analysis tool to simulate the effect of equipment aging and usage on reliability. A model was developed for assessing station reliability through assigning failure probabilities to all equipment and modeling their relationships. The adequacy of the current station facilities in term of supply reliability can be obtained and compared to the required reliability performance index or reliability performance curve which was defined in term of outage frequency and duration. End-of-life failure probability for diesel generation unit has been derived based on its actual maintenance history and age profile. The proposed method was implemented on an existing diesel generating station and the results show that not only can it demonstrate the reliability performance level the current station can achieve, but also provide an clear indication whether any aging unit can be retired or need to be replaced in order to maintain the adequate supply reliability of the station.
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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) | 0.000 | 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".