Bibliographic record
Abstract
Upward trend of the electricity consumption lead to concerns in this field.Due to limitation of the system, it is impossible to add new power lines and make the network larger at times to satisfy the demand.Therefor using renewable energy resources seems a reasonable solution to overcome such issue.The renewable energy sources, as an a lternative as well as promising energy source, however by connecting this type of energy source new challenges are came to the power grid.The fluctuation of the output power of the wind energy due to environmental condition is one of the examples.In the same way, wind power injection into an electric grid affects the power quality due to the fluctuating nature of the wind.Power quality issues such as: voltage dip, harmonic distortion and reliability problems are among concerns in the grid caused by wind variations.Flexible AC Transmission Systems (FACTS) use Thyristor controlled devices and optimally utilizes the existing power networks.FACTS devices plays an important role in controlling the reactive and active power flow to the power network, and henc e, both transient stability and fluctuation in the systems voltage.This paper proposes a state feedback controller for Static VAR controller (SVC), as the controller act as a state feedback in order to enhance the power electronic -based device with ability y to damp the Low Frequency Oscillation (LFO).The control has the ability to control and increase the power quality of the network connected to the high wind power penetration by controlling the active and reactive power of the grid from far distances.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.994 | 0.983 |
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; both teacher heads agree on what is shown here.
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".