A Modified AGC for Power System in the Presence of Grid Following Inverters
Bibliographic record
Abstract
Due to the significant growth of the penetration level of inverter-based resources in power transmission grids, the role and impact of these resources in maintaining the stability of the network can no longer be ignored. Therefore, for this category of resources, a role similar to traditional power plants should be considered in controlling the stability of the network. Accordingly, the purpose of this paper is to propose an algorithm to improve the performance of an automatic generation control system (based on a PI controller) in the presence of grid-following inverters to use their maximum potential and ability in network stability in the structure of an automatic generation control system and next to conventional power plants. Therefore, the decoupled-PQ control system (grid-following based) is considered for implementation in a three-area automatic generation control system structure. The dynamic simulation results were performed in an IEEE 39-bus test system using DIgSILENT PowerFactory software and its DSL environment. The results of these dynamic simulations show the effectiveness of this method to improve the automatic generation control system performance and system stability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".