A Framework to Assess and Analyze Enhancement Options for Microgrid Resiliency against Extreme Wind
Bibliographic record
Abstract
The objective of a power system is to provide electricity to its customers as economically as possible with an acceptable level of reliability while safeguarding the environment. Power system reliability assessments are routinely performed to ensure adequate system resources and reliable operation using well-established methods, quantitative metrics, regulatory standards and compliance incentives in the jurisdictions of responsibilities. The alarming increase in the occurrence of extreme events, which are not included in routine reliability evaluation, has raised growing concerns due to the catastrophic impacts of these events on distribution systems. The potential economic losses due to prolonged and large-scale outages have motivated utility planners, operators and policy makers to acknowledge the importance of system resiliency against such events. Power system resiliency, however, lacks widely accepted modeling frameworks, standards, assessment methods and metrics. This paper presents a resilience assessment framework, along with quantifiable metrics to assess the resiliency of a distribution system against extreme winds, which are among the most common form of natural disasters affecting the North American region. The paper assesses the effectiveness of infrastructural and operational resilience enhancement strategies. The effectiveness of preventive and corrective strategies is also analyzed on a test distribution system.
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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".