Enabling decentralized real-time analysis of smart distribution systems using wireless communication
Bibliographic record
Abstract
Wireless communications, distributed intelligence and automated control systems are the key technological components in achieving the goals of the smart grid, e.g. self-healing, optimum operation, and power quality. In this paper, we are proposing a novel approach that utilizes wireless communications to enable decentralized real-time analysis of distribution systems. Each bus (node) in the distribution system has a processing unit that communicates with other relevant nodes in the system. Each processing unit performs a part of the overall analysis, and forwards the results to relevant nodes. The proposed framework has been implemented using GNU-Octave, and the Network Simulator NS-3. GNU-Octave was used to verify the validity, accuracy and speed of the framework. A WiMAX network was used as the communication layer, and NS-3 simulations captured the WiMAX network performance, e.g. average packet delay, average packet delivery ratio, and average convergence times for different number of nodes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".