Relationship between the System’s Flexible Adjustment of Power Supply Ratio and the System’s New Energy Operation and Consumption Capacity Based on Data Analysis
Bibliographic record
Abstract
In an energy plan with a high rate of renewable energy acquisition, the comprehensive development of wind and solar energy and flexible power sources such as energy storage will play a key role in this process. The power supply structure in some areas is dominated by coal power, and there is a serious shortage of flexible power supply, which hinders the development of renewable energy. Therefore, this paper proposed a new energy operation and consumption planning method considering the flexible adjustment of the power supply ratio. This paper established a two-layer power planning model with the lowest cost to the whole society and the largest consumption of renewable energy. Then, based on the copula theory, a wind-solar combined consumption probability model is established, and the new energy output curve of the planning year is predicted. Finally, the power supply optimization was solved by the Hooke-Jeeves iterative method. The experimental part took a certain region as the research object, setting the proportion of flexible power supply to 24%. It found out the newly installed capacity of various power supplies, and compared the actual data in the region. The research results have shown that increasing the proportion of flexibly regulated power supply can effectively improve the operation and absorption capacity of new energy, the wind abandonment rate is reduced by 6.21%, and the light abandonment rate is reduced by 5.38%.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".