Small-signal dynamic model of a micro-grid including conventional and electronically interfaced distributed resources
Bibliographic record
Abstract
A systematic approach to small-signal modelling of a micro-grid system that includes conventional (rotating machine) and electronically interfaced distributed resource (DR) units is presented here. The proposed approach incorporates fundamental frequency deviations in the overall system model and provides a methodology for the analysis of autonomous micro-grid, which inherently is more prone to frequency changes than the conventional utility grid. The model represents (i) electro-mechanical dynamics of the synchronous machine including the exciter and the governor systems, (ii) dynamics of the voltage-sourced converter and its real/reactive power controllers and (iii) the network dynamics. The model is intended for the controller design/optimisation, evaluation of angle/voltage stability, investigation of torsional dynamics, controller interactions of electronically interfaced DR units and low-frequency power quality issues. Typical results from application of the proposed modelling approach to a study system are presented. The results are qualitatively verified on the basis of the comparison with those obtained from time-domain simulation in the PSCAD/EMTDC environment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".