Incorporating reliability index distributions in small isolated generating system reliability performance assessment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Probabilistic techniques are widely used in power system reliability evaluation. The average or mean values of a wide range of indices are used to assess the reliability of generation, transmission and distribution systems. These mean values are extremely valuable and are the primary indices in generation adequacy studies of power systems containing both conventional generating units and unconventional energy sources such as wind and solar energy. Additional information can, however, be created, which can prove useful in a wide range of systems and applications. The probability distributions associated with the reliability indices can be used as supplemental measures and provide valuable information for system planners and operators. This paper presents the results of a series of studies on reliability index distributions for small isolated power systems using wind energy and storage facilities. Reliability index distributions associated with generating capacity adequacy parameters such as the loss of load expectation (LOLE), expected outage frequency (EOF), expected energy supplied by the battery (EESBB) and battery discharging frequency (BDF) etc. are presented and examined.
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.
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 | 0.001 |
| 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