Practical application of waveform relaxation method for testing remote protective relays
Bibliographic record
Abstract
Testing of newly designed protective relay logics is essential prior to the installation of the relay hardware in power systems. Real-time simulators (rts) are widely used to simulate the computer models of the power system in real-time to analyze the closed loop performance of the relay. This kind of simulation is expensive because high performance processing units are required for the rts systems. Also, the closed loop simulation results will be inaccurate if there are communication delays between the rts and the relay hardware. In this paper, a new iterative method for the closed loop performance test of protective relays is presented. The approach uses the iterative method of the Waveform Relaxation (WR) with the use of a specialized interface hardware called the Real-Time Player/Recorder (RTPR). The power system model is simulated in an off-line electromagnetic transient (EMT) simulation program and the relay hardware is connected to the RTPR device. The off-line simulation results (waveforms) are recorded and then played back in real-time to the relay through the RTPR device. The RTPR records the relay response (trip signals) accordingly and makes them available to the EMT simulation. The EMT simulation is once again repeated with the new recorded waveforms and the results are compared with those from the previous iteration. If the waveforms are different, the above process is repeated. The converged results represent the closed loop response of the EMT simulation and the relay hardware. The approach is used to test the reclosing function of a commercially available relay (SEL-421). It is shown that some of the relay settings must be adjusted to facilitate this type of simulation. The relay is also tested by a real-time digital simulator for cross-validation of the proposed approach. Very similar results prove the high accuracy of the proposed method.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".