REMEDIAL ACTION SCHEME FOR WIND POWER INJECTION WITH MINIMUM TRANSMISSION LINE LOSS, 1-10.
Bibliographic record
Abstract
The rise in power demands and concern over climate change is leading to increased penetration of wind energy into the grid.However, the transmission network infrastructure is not equipped for such a transition.Transmission lines are responsible for the transfer of electric power from generating stations to load centres and consumers.In this process, the lines incur losses which affect the quality of power.Also, it has an economic impact on the utilities.Therefore, such losses must be minimised so that the power quality can be improved and economic losses are less.With the increase in the percentage of wind energy integration in the grid, the transmission line losses are increasing.To address this problem, a remedial action scheme (RAS) has been proposed for increasing wind energy penetration in the grid with minimum transmission line losses.To achieve this, the proposed method uses a multiobjective optimisation problem which is solved using the genetic algorithm.For varying transmission line losses, the multi-objective optimisation problem determines the optimal generation from each wind generator.The proposed RAS is tested for the New England 39-bus network and the results highlight the performance of the method to maximise the wind power injection.
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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".