Analysis and Prediction on the Development Potential of Pumped Storage Hydroelectricity in China in Ten Years (2022 - 2032)
Bibliographic record
Abstract
Pumped Storage Hydroelectricity (PSH) is a very important method for energy storage. The cycle of water usage, starting with using excess energy, is of great significance for saving energy and improving social and economic benefits. This paper focuses on the analysis and prediction for the ten years' development potential of PSH in China. By analyzing the basic principles and computation methods to understand how PSH works. There are introductions and explanations of two huge PSH projects to determine the current advantages and suggest improvements. Based on China's current national conditions and geographical regions, PSH is suitable and being promoted to be developed, and it will help the country reach the objective of carbon peaking by 2030 and carbon neutrality by 2060. By comparing PSH to its potential competitor, Solid Gravity Energy Storage (SGES), the advantages of maturity and applicability of PSH in China allows PSH to be developed better. Therefore, the thesis evaluated the PSH's future development and concluded that this technology should be promoted in the future.
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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 | 0.002 | 0.003 |
| 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".