Synchronized Phasor Measurements with GPS Time Stamping using 64 Point DFT in PMU
Bibliographic record
Abstract
This paper describes about the time synchronization of different locations voltage or current signals for accurate comparison of signals on single phasor graph, all the measured phasors are synchronized with Global Positioning System (GPS) time stamping. Day to day power demand increases very rapidly, to meet the growing demand of electrical energy new energy resources are required and manage them efficiently. For efficient allocation of sources there should be a good monitoring and fast control system. For better monitoring and control of the system accurately it requires “Wide Area Monitoring” of power system. In the wide area monitoring system collection of data from the power system should be at a faster level. The collection of data from the power system at faster level is possible by using “Phasor Measurement Units(PMUs)”. PMU collects the data at faster rate rates like 50-60 samples for cycle, this information is send to local Phasor Data Concentrator (PDC). Local phasor data concentrator collects the data from different PMUs which are located in different areas. This PDC helps to take the necessary action on power system. For synchronization, pulse per second(PPS) is taken from GPS module. From this 1PPS, 3200 pulses is generated for high accuracy of 64 point DFT of 50Hz signal using microcontroller. System frequency is calculated by using time period between the two consecutive raising edges or falling edges of square wave. This is in synchronous with the input sinusoidal signal.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".