Power Swing in Systems With Inverter-Based Resources—Part I: Dynamic Model Development
Why this work is in the frame
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Bibliographic record
Abstract
While power swing is a well-understood phenomenon in conventional power systems, the power swing characteristics of systems with inverter-based resources (IBRs) remain significantly under-theorized. This paper demonstrates that this knowledge gap carries practical ramifications, including the potential to undermine the stability and reliable protection of future grids, where swing dynamics can be heavily influenced by IBRs. The paper investigates power swing in systems with IBRs in two parts. Part I of the paper develops the necessary relations to devise a novel state-space model for systems with IBRs. This analytical model is necessary to (i) quantitatively identify the distinct characteristics of power swings in IBR-rich grids, and (ii) theoretically prove that these characteristics can be generalized. The paper highlights fundamental differences between this new model and the well-established model for power swings in systems that consist solely of synchronous machines (SMs). To reveal the features of power swing in systems with mixed generation types, the paper also systematically incorporates the dynamic equations of SMs into the developed model. The accuracy of the proposed model is evaluated against PSCAD/EMTDC simulation results for a benchmark test system that includes multiple IBR plants and their detailed control systems. Part II of the paper will build upon the findings from Part I to investigate the implications of the specific features of IBRs' power swing from the perspective of power system protection.
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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 it