Active and Reactive Power Sharing of Two Parallel Inverters Using Combination of Virtual Synchronous Generator and Droop Control.
Bibliographic record
Abstract
The concept of active, reactive, and harmonic distortion powers sharing of two inverters connected in parallel to the main grid becomes a very important problem for security of supply. The first contribution presented in the paper is the combination of a virtual synchronous generator (VSG) and a nonlinear current control technique. The VSG controls the active powers sharing between the two inverters and contributes to the reduction of the frequency deviation at the point common coupling (PCC) during the variation of the load or the injection of solar PV active power to the grid. The VSG improves the inertia and damping of the system and makes the system robust with better frequency stability. The Droop control estimates the active power of the power of the battery energy storage system (BESS), the VSG injects this active power estimated at the PCC point to reduce the frequency deviation. The second contribution concerns the non-linear control making it possible to compensate and to share the current harmonics between the two inverters and allows the reactive power sharing between the two inverters. The concept of combining a VSG and nonlinear control offers several possibilities and makes it possible to decouple the active and reactive powers sharing of the two inverters. The nonlinear control approach guarantees reactive power compensation in the grid side. Finally, the results obtained by simulation show the relevance of the proposed approach of power sharing, reduction of frequency deviations and system stability robustness.
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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) | 0.000 | 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 | 0.000 | 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".