Interaction Dynamics and Active Suppression of Instability in Parallel Photovoltaic Voltage-and Current-Source Converters Connected to a Weak Grid
Bibliographic record
Abstract
Parallel operation of power electronic converters is becoming popular in utility-scale photovoltaic (PV) systems. However, the literature does not cover the interaction dynamics and stabilization of parallel PV-based voltage- and current-source converters (VSC and CSC) connected to a weak grid. To fill in this gap, this article characterizes the dynamic interactions among the parallel PV-based VSC and CSC systems considering the effects of the PV source dynamics, grid strength, operating point variation, and control parameters. A detailed small-signal model of the parallel system is developed and used to characterize the dynamic interactions using eigenvalue and input/output impedance-based analyses. The study showed that undesirable converters interactions are yielded, the dc-links stability is reduced, and the parallel system cannot inject 1.0 p.u. of active power at unity short-circuit ratio (SCR). Therefore, an active stabilization approach is proposed for the parallel VSC-CSC system to reduce the interactions, improve stability, and facilitate 1.0 p.u. of active power injection at unity SCR. Detailed nonlinear time-domain simulations and real-time simulation results verified the accuracy of the analytical results and the effectiveness of the proposed stabilization method under a wide range of operating conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".