Fuzzy Logic Based Adaptive Overcurrent Protection for Wind Farms
Bibliographic record
Abstract
Despite recent technological advancements in wind farms, simple protection schemes are still being applied to wind farms which are non-optimal and unsatisfactory resulting in maloperation of relays. Consequently, the maloperation causes different levels of damage to power components in the plant during fault. Furthermore, due to the intermittent nature of wind farms, the generated current feeding the grid during extreme high and low wind speeds, creates a significant difference in magnituds of the generated current. Thus, existence of only one group of settings for the overcurrent relays (OCRs) would cause drastic miscoordination and false tripping during fault. In order to solve these issues, this paper proposes an effecient adaptive overcurrent protection and coordination for large-scale wind farms using rule-based fuzzy logic controller (FLC) scheme. In order to test the performance of the proposed FLC scheme several OCRs based on standard Schweitzer Engineering Laboratories industrial protection relay (SEL-751) are developed in Matlab/Simulink. A large-scale wind farm model is also developed to perform fault analysis, relay setting and coordination calculation. FLC is developed to provide adaptive feature for the relays so that the OCR group settings for each relay are intelligently updated according to the variation of wind speed. The performance of the proposed FLC protection scheme is found robust, reliable, efficient and satisfactory.
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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) | 0.000 | 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".