Viability of powerline communication for the smart grid
Bibliographic record
Abstract
There is currently an ongoing debate surrounding what would be the best choice for smart grid communication technology. One of the promising communication technologies for smart grid realization is Powerline Communication (PLC). However, because of its noisy environment and the low capacity of Narrowband Powerline Communication, its viability for smart grid realization is being questioned. To investigate this issue, we studied smart grid communication network requirements. We categorize smart grid data traffic into two general traffic classes including home area network data traffic and distribution automation data traffic. Then using network simulator-2, we simulate powerline communication and a smart grid communication network. To have a better understanding of the viability of powerline communication for smart grid realization, some future smart grid advanced applications are considered. Latency and reliability are considered to be the main smart grid communication network requirements. In this paper, the delay of different traffic classes under different network infrastructures and traffic applications have been calculated. Furthermore, a viable powerline communication network infrastructure for smart grid communication network is proposed.
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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 | 0.003 |
| 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 | 0.002 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".