FPGA implementation of a phaselet method for high speed distance relaying — Preliminary results
Bibliographic record
Abstract
Fault clearing time is critical to the safety of power system equipment. Most state-of-art distance relays operate at the speed of one cycle or even longer. There are a few sub-cycle algorithms such as half-cycle type Fourier, least error square, traveling wave, and wavelet type methods. This paper utilizes a sub-cycle (phaselet) method for estimation. The algorithm and testing with IEC 61850 Sampled Value and GOOSE communication protocols was discussed in detail in the recently accepted paper by the authors in the IEEE Transactions on Smart Grids [1]. The main focus of this paper is on the hardware implementation of the phaselet method on field programmable gate arrays (FPGAs) to achieve high speed and the hardware-in-the-loop testing. The FPGA implementation of the method helps in parallelizing the algorithm and provides fast computation speed compared to sequential execution on digital signal processor (DSP). The algorithm is implemented on Xilinx Virtex 6 board. The FPGA relay is tested using hardware-in-the-loop simulations with a real time digital simulator (RTDS).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".