International Electronical Committee (IEC) 61850 Mapping with Constrained Application Protocol (CoAP) in Smart Grids Based European Telecommunications Standard Institute Machine-to-Machine (M2M) Environment
Bibliographic record
Abstract
As power systems develop rapidly into smarter and more flexible configurations, so too must the communication technologies that support them. Machine-to-machine (M2M) communication in power systems enables information collection by combining sensors and communication protocols. In doing so, M2M technology supports communication between machines to improve power quality and protection coordination. When functioning in a “smart grid” environment, M2M has been labelled by the European Telecommunications Standard Institute (ETSI). International Electronical Committee (IEC) 61850 as the most important standard in power network systems. As evidence, this communication platform has been used for device data collection/control in substation automation systems and distribution automation systems. If the IEC 61850 information model were to be combined with a set of contemporary web protocols, the potential benefits would be enormous. Therefore, a constrained application protocol (CoAP) has been adopted to create an ETSI M2M communication architecture. CoAP is compared with other protocols (MQTT, SOAP) to demonstrate the validity of using it. This M2M communication technology is applied in an IEC61850, and use the OPNET Modeler 17.1 to demonstrate intercompatibility of CoAP Gateway. The proposed IEC 61850 and CoAP mapping scheme reduces the mapping time and improves throughput. CoAP is useful in the ETSI M2M environment where device capability is able to be limited.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".