Development of coordinated control method based on Graph search method between EV and DG for voltage regulation
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
• Coordinated control between DGs and EVs addresses voltage problems in distribution systems. • Graph Search Method (GSM) optimizes reactive power control to resolve local voltage issues. • The proposed method enhances robustness to topology changes and reduces system losses. • Active power control is applied when reactive power alone cannot solve voltage problems. • OpenDSS and MATLAB integration verifies the performance of the proposed voltage control method. In this paper, a study is conducted to solve voltage problems that may occur, when large-scale Distributed Generations (DGs) and Electric Vehicles (EVs) are connected to the distribution system, through coordinated control between DGs and EVs. Using the Graph Search Method (GSM), the voltage problem was solved through the reactive power control of EVs and DGs in the near area where the voltage problem occurred. As a result, it was possible to obtain a result with high robustness against the change of the topology and reduction of the total loss of distribution system. In addition, when the voltage problem cannot be solved by only reactive power control, the active power control was performed for EVs and DGs included in a specific divided system of the conventional distribution system using the GSM to maintain the voltage within the normal range. Finally, to verify the performance of the proposed method, the whole algorithm was implemented by linking the Open Source Distribution System Simulator (OpenDSS), and the MATLAB.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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