New Heat Energy Trading Concepts for the Next Generation Smart Grids
Bibliographic record
Abstract
Modern electric power systems are heavily structured based on digital technology. Starting from the production point to the consuming point, all the sensing devices have a two-way communication that allows for quick and smooth actions to monitor, control, optimize, and protect the corresponding electric power grid with a fast response to any change in the system status. During the winter season, especially in cold countries, a big portion of non-electric energy is consumed for heating purposes. Such these alternative energy sources are: logs, solar, and biogas water heaters. In smart grids, the local trading strategy is possible between two entities, where the one that has a surplus energy can transfer it to others. However, the preceding non-electric forms of energy are still not traded between entities. This paper presents a new concept on how to make this type of nonclassical energy trading possible between entities. This concept can be considered as a basis for solving the missing link in managing electric and non-electric forms of energy in the next generation smart grids.
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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 | 0.000 | 0.000 |
| 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".