An Efficient Peer-to-Peer Energy-Sharing Framework for Numerous Community Prosumers
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Bibliographic record
Abstract
This article presents an efficient peer-to-peer energy-sharing framework for numerous community prosumers to reduce energy costs and to promote renewable energy utilization. Specifically, for day-ahead and real-time energy management of prosumers, an intercommunity energy-sharing strategy and an intracommunity energy-sharing strategy are proposed, respectively. In the former strategy, prosumers can share energy with any community peers, and community aggregators represent their own prosumers to coordinate energy sharing. A two-phase model is designed. In the first phase, the optimal energy-sharing profiles of prosumers are derived to minimize the global energy costs, and in the second phase, equilibrium-based energy-sharing prices are induced considering the individual interests of prosumers. In the latter strategy, prosumers share energy only with its community peers for time saving to handle real-time uncertainties collaboratively to reduce real-time costs. The framework efficiency is verified by the simulation cases on a typical distribution network.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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