Performance of the Precision Time Protocol for clock synchronisation in smart grid applications
Bibliographic record
Abstract
ABSTRACT Accurate time stamping is essential for reliable operation of the automation and control systems used across a smart grid. This paper investigates the performance of the Precision Time Protocol (PTP) for time distribution over the telecommunication networks interconnecting such systems. Distributed clocks are arranged in a PTP master‐slave hierarchy and can be synchronised to an international time standard with sub‐microsecond accuracy. Using Hydro Québec's telecommunications facilities, we investigate the synchronisation error that is observed using some of the latest PTP clock prototypes over a widely spread network. As such, field trials are performed by deploying PTP master and slave clocks in distant sites of Hydro Québec's wide area network (WAN). A thorough analysis of these trial outcomes is further conducted using laboratory experiments that point out the impact of different parameters such as the PTP messages rate, as well as the link bandwidth and asymmetry. Our analysis leads to important criteria for optimal PTP system design in a WAN environment using appropriate clock and network parameter settings. Improving the PTP clocks internal features is also part of this optimal design, since it is necessary for maintaining the required synchronisation performance in power grid applications running under scarce communication network bandwidth conditions. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".