Understanding the cost of power interruptions to U.S. electricity consumers
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
The massive electric power blackout in the northeastern United States and Canada on August 14-15, 2003 resulted in the U.S. electricity system being g called antiquated and catalyzed discussions about modernizing the grid. Industry sources suggested that investments of $50 to $100 billion would be needed. This report seeks to quantify an important piece of information that has been missing from these discussions: how much do power interruptions and fluctuations in power quality (power-quality events) cost U.S. electricity consumers? Accurately estimating this cost will help assess the potential benefits of investments in improving the reliability of the grid. We develop a comprehensive end-use framework for assessing the cost to U.S. electricity consumers of power interruptions and power-quality events (referred to collectively as reliability events ). The framework expresses these costs as a function of: - Number of customers by type in a region; - Frequency and type of reliability events experienced annually (including both power interruptions and power-quality events) by these customers; - Cost of reliability events; and - Vulnerability of customers to these events. The framework is designed so that its cost estimate can be improved as additional data become available. Using our framework, we estimate that the national cost of power interruptions is about $80 billion annually, based on the best information available in the public domain. However, there are large gaps in and significant uncertainties about the information currently available. Notably, we were not able to develop an estimate of power-quality events. Sensitivity analysis of some of these uncertainties suggests that the total annual cost could range from less than $30 billion to more than $130 billion. Because of this large range and the enormous cost of the decisions that may be based on this estimate, we encourage policy makers, regulators, and industry to jointly under take the comparatively modest-cost improvements needed in the information used to estimate the cost of reliability events. Specific areas for improvement include: coordinated, nationwide collection of updated information on the cost of reliability events; consistent definition and recording of the duration and frequency of reliability events, including power-quality events; and improved information on the costs of and efforts by consumers to reduce their vulnerability to reliability events.
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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 | 0.001 |
| 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