Bi-Level Transactive Coordination of Energy Management Systems in a Community
Bibliographic record
Abstract
This paper presents a hierarchical coordination scheme for residential customer groups with flexible assets in a community through a transactive energy architecture. The work designs a framework to manage home energy management systems (HEMSs) in a residential group to reduce the grid’s stress by optimizing the aggregated consumption and improving the load factor. Nevertheless, addressing the specific challenges in different layers of the distribution system needs a hierarchical framework to guarantee lower-level (groups) and upper-level (community) objectives. Thus, this paper also develops the HEMSs coordination in a group into a hierarchical one with demand response-enabled electric heaters in a community comprising two residential groups. The presented framework includes two local coordinators at the lower level managing their associated HEMSs and a community coordinator at the upper level handling the community. The functionality of the proposed method has been investigated and compared with dynamic price, independent group coordination, and without applying demand response program cases. The proposed approach can reduce the community’s peak energy consumption by up to 47.5%.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".