40 | Fourth Quarter 2013 Politics of Power in China: Institutional Bottlenecks to Reducing Wind Curtailment Through Improved Transmission
Bibliographic record
Abstract
Grid-connected wind capacity has increased thirty-fold in China in the six years since the Renewable Energy Law was passed. At the end of 2012, China led the world in cumulative wind installations with 63 gigawatts (GW), while approved projects planned or under construction exceeded 44 GW (He, 2013). Despite the lead in capacity, however, China generated 30 % less electricity from wind than the United States, which was a close second in terms of total installations. Reduced capacity factors have been attributed to high amounts of forced curtailment, which reached as high as 50 % in some regions last year. The causes of curtailment are manifold: high penetrations of wind in provinces far from load centers, inflexibility of the coal-heavy generation mix, and institutional barriers owing to incomplete power deregulation. To address these shortfalls and other chronic power challenges, China’s grid companies propose to significantly expand long-distance ultrahigh-voltage (UHV) interconnections as well as strengthen interprovincial and intraprovincial ties. These will report-edly double wind utilization by 2020 (State Grid, 2010). However, institutional hurdles to better integrat-ing wind, ranging from an intense debate within China over the future structure of the grid to inflexible transmission operation and pricing, threaten to delay or derail benefits of interconnection. Overview of Current and Proposed Transmission Network
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".