Windpower Resource Screening for The Western U.S. Region
Bibliographic record
Abstract
ABSTRACT This article describes a comprehensive screening study performed in 2007 to identify wind energy resources in the 14-state Western Electric Coordinating Council (WECC). WECC comprises the entire Western Interconnection. With a footprint of 1.8 million square miles within the U.S., two Canadian provinces, and Baja Norte, Mexico, WECC offers significant but widely dispersed potential for farming wind resources. The methodology described in this article is novel but tested in application. Using resource maps of greatest wind potential, electric generation is incrementally increased to reach a regional 25% penetration target. This approach allows overloaded transmission corridors to be identified that will require investment to reliably ship power to the areas of greatest demand growth. In this study, resolution is based on 1 km cells. Explicit consideration is given to reserve transmission capacity to estimate WECC's ability to move power from remote sites. Wind resource assumptions are based on National Renewable Energy Laboratory (NREL) wind maps, Class 3 or higher (mean annual wind speeds = 6.9 m/s at 80 m). The wind resource is converted on the basis of generating clusters of 77-meter diameter, 1.5-MWe turbines with a capacity factor of 48%. Limits are placed on distance to load centers to avoid transmission congestion and to implicitly acknowledge an economic breakeven towards lower speeds and closer distance.
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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 | 0.001 | 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".