An Enhanced Instantaneous Circulating Current Control for Reactive power and Harmonic Load Sharing in Islanded Microgrids
Bibliographic record
Abstract
To address inaccurate load demand sharing problems among parallel inverter-interfaced voltage-controlled distributed generation (DG) units in islanded microgrids with different DG power ratings and mismatched feeder impedances, an enhanced voltage control scheme based on actively compensation of circulating voltage drops is proposed in this paper. Using proposed strategy, reactive power and harmonic currents sharing are shared accurately and proportionally without knowledge of feeder impedances. As the proposed local controller consists of two well-separated fundamental and harmonic voltage control branches, the reactive power and harmonic currents can be independently shared without having remarkable effects on the amplitude and quality of the DGs voltage, even if nonlinear (harmonic) loads are directly connected at the output terminal of units. In addition, the accurate load sharing can also be attained when the plug-and-play performance of DGs and various loading conditions are applied to the system. The effects of communication failures and latency on the performance of proposed strategy are also explored. Design process of the proposed control system is presented in detail and comprehensive simulation studies on a three-phase microgrid are provided to validate the effectiveness of the proposed control method.
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 | 0.001 | 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".