Value-based distribution system reliability planning
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
Society is becoming increasingly dependent on a cost-effective reliable electric power supply. Unreliable electric power supplies can be extremely costly to electric utilities and their customers. Predictive reliability assessment combines historical outage data and mathematical models to estimate the performance of specific network and system configurations [e.g., IEEE Std. 493-1990]. This paper is concerned with the value-based assessment of proposed modifications to an existing industrial distribution system configuration to minimize the costs of interruptions to both the utility and its industrial customers. This paper presents a series of case studies of an actual industrial load area supplied by two feeder circuits originating from two alternate substations. Each case study reveals the impact on the cost of industrial load point interruptions and the frequency and duration of industrial load point interruptions when various system constraints (e.g., ideal and nonideal protection coordination schemes, substation capacity restrictions, etc.) are imposed on the distribution system. The paper discusses in some detail the variance in reliability performance indices and their impact on the cost of load point interruptions. A basic conclusion of this paper is that expansion plans of an industrial distribution system can be optimized in terms of reliability by using an economic criterion in which the sum of both the industrial facility interruptions and the utility system costs are minimized.
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 | 0.000 | 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) | 0.000 | 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