Electric power transaction of electric vehicle based on smart contract and double auction
Why this work is in the frame
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Bibliographic record
Abstract
The increase of the number of electric vehicles leads to serious valley imbalance in the power grid. In order to achieve peak cutting and valley filling, according to the energy storage characteristics of electric vehicles, this paper proposes an electric vehicle group (EVG) energy trading method based on smart contract and double auction matching mechanism, and constructs the electric energy transaction process of the electric vehicle and electric vehicle in the electric vehicle group under the unbalanced load of the power grid. Through deploying the double auction matching algorithm to the smart contract, the automatic execution of matching transaction and automatic clearing of transaction cost are realized, which saves the economic cost of manual matching mode. In addition, the multi-stage quotation method proposed greatly improves the number of transactions. The simulation experiment based on Monte Carlo simulation shows that the power transaction method can not only effectively alleviate the valley problem of power grid load, achieve the effect of reducing and raising Valley, but also can improve the transaction efficiency.
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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