Implementing self-healing distribution systems via fault location, isolation and service restoration
Bibliographic record
Abstract
BC Hydro and Powertech have developed a real-world outdoor integration and interoperability test yard for distributed automation technologies at Powertech Labs referred to as the Smart Utility Test Center (SUTC). The SUTC contains live 25kV power distribution equipment, telecommunications, data collection and management systems interconnected with a commercial Distribution Management System (DMS). FLISR (Fault Location, Isolation and Service Restoration) is a Distribution Management System feature to support implementation of self-healing power distribution systems. This presentation will provide an overview of the FLISR as well as the practical aspects of modeling power system networks to support FLISR functions. This paper also discusses how the DMS power system models and FLISR applications are optimized in the SUTC environment to improve the accuracy and performance of self-healing configurations. A sample case study of improvement in SAFI and SAIDI is presented based on an outage simulation with and without self-healing.
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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) | 0.000 | 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".