RTCE: Real-Time Co-Emulation Framework for EMT-Based Power System and Communication Network on FPGA-MPSoC Hardware Architecture
Bibliographic record
Abstract
With the expansion of smart grid infrastructure world-wide, modeling the interaction between power systems and communication networks becomes paramount and has created a new challenge of co-simulating the two domains before commissioning. Existing co-simulation methods mostly concentrate on the off-line software-level interface design to synchronize messages between the simulators of both domains. Instead of simulating in software with a large latency, this article proposes a novel real-time co-emulation (RTCE) framework on FPGA-MPSoC based hardware architecture for a more practical emulation of real-world cyber-physical systems. The discrete-time based power system electromagnetic transient (EMT) emulation is executed in programmable hardware units so that the transient-level behaviour can be captured in real-time, while the discrete-event based communication network emulation is modeled in abstraction-level or directly executed on the hardware PHY and network ports of the FPGAMPSoC platform, which can perform the communication networking in real-time. The data exchange between two domains is handled within each platform with an extremely low latency, which is sufficiently fast for real-time interaction; and the multi-board scheme is deployed to practically emulate the communication between different power system areas. The hardware resource cost and emulation latency for the test system and case studies are evaluated to demonstrate the validity and effectiveness of the proposed RTCE framework.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".