A User-centric Approach toward Resilient Frequency-regulating Wind Generators
Bibliographic record
Abstract
Smart microgrids are rapidly being developed and deployed, even as concerns over their cyber-physical security are increasing. The high penetration of these power electronic-interfaced energy resources has resulted in weaker power grids and an increase in cyberattack surface. The implementation of frequency regulation in these new resources—particularly in wind generators—is on the rise. This article investigates how malicious controllable loads can threaten the integrity of frequency-regulating wind generators. Adopting a user-centric approach and benefiting from small-signal analyses, the article shows for the first time how these wind generators can be the target of attackers. Effective methods to enhance system resilience are sought by mitigating the attack risk in the extended end-users, wind generators. The article models and explores how proper tuning and design of the physical system can improve cyber-physical security. The work also extends the user-centric method to the physical layer of smart grids. Detailed time-domain simulations verify the results of the analyses.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".