Effective Capacitor Control Model for Unbalanced Distribution Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The author proposes an effective capacitor control model for unbalanced radial and meshed distribution systems. Due to the linear characteristic of the proposed model, a constant sensitivity matrix relating the incremental capacitor shifts and system status can be derived, and then the sensitivity-based objective function and network constraints can be obtained. The linear formulation can be solved by the commonly used linear programming and integer programming techniques, which are among the best choices for real-time control in terms of computational speed, reliability, and ability to handle many different operating constraints. The development of the sensitivity matrix does not need any assumptions about voltage magnitudes, voltage angles, line r/x ratios, and network topology; thus, the proposed method can achieve high robustness and accuracy. The proposed capacitor control model can be used to solve the capacitor placement and real-time capacitor control problems; however, in order to verify the accuracy of the model, only the corrective dispatching problem is solved in this work. Test cases including the unbalanced radial and meshed distribution systems and a large-scale distribution system acquired from Taiwan Power Company are all conducted. Test results show that the proposed method can effectively handle the capacitor control problems and has great potential to be integrated into distribution automation.
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.
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 it