Transient Stabilization Control of Electric Synchronous Machine for Preventing the Collapse of DC-Link Voltage
Bibliographic record
Abstract
Electric synchronous machine (ESM) control is a power synchronization strategy that utilizes the measurement of dc-link voltage to generate a frequency reference. By using ESM, the grid-connected inverters with indeterminant renewable energies can work in grid-forming mode, and realizes a closed-loop control of the dc-link voltage. However, under weak grid conditions, the ESM provides a sluggish performance for the regulation of dc-link voltage and is prone to the transient instability issues, including dc-voltage collapse and synchronization instability, which hinders the application of ESM. This paper reveals the instability mechanism of dc-link voltage under large disturbances, and proposes a passivity-based control for the transient stabilization of ESM. Firstly, the transient stability of ESM is analyzed from the view of port-Hamilton system. The corresponding energy function comprises the energy stored in dc-link capacitor and potential energy in ac side. Then, a 2-degree-of-fredom controller is proposed to stabilize the dc-link voltage by enhancing the energy dissipation. It combines a phase-shift controller and supplementary voltage controller, fully utilizing the control flexibility of the inverters. Dissipation analysis proves the large-signal stability of the proposed control. Simulations and hardware-in-the-loop (HIL) experiments validate its transient performance in a single-inverter-infinite-bus (SIIB) system and a multi-inverter test system.
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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) | 0.000 | 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) | 0.001 | 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 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".