A New Electronic Load Controller for the Self-excited Induction Generator to Decrease Stator Winding Stress
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
Constant voltage and frequency can be generated by a Self-Excited Induction Generator (SEIG) driven with a fixed-speed low-head hydro-turbine when a constant electrical load is maintained by an Electronic Load Controller (ELC). In the Conventional-ELC (C-ELC), usually a chopper with a dump load is used in parallel with the consumer loads to provide regulation of voltage and control of frequency. In the C-ELC configuration a high degree of stress can be experienced by stator windings and excitation capacitors resulting from chopper operation, since in each chopping period the dump load is connected to the stator winding for a short period then disconnected. A new ELC topology is proposed to reduce this stress. Compared with the C-ELC, the main dump load has been divided into two separated parts. A part of the dump load can be connected in parallel with the consumer loads, resulting in less variation in the total load seen by the SEIG and less stress on the stator windings and excitation capacitors. This proposed topology can be utilized per-phase using bi-directional power switches, hence it can operate with unbalanced consumer loads. Simulation results demonstrate that even with unbalanced three-phase loads (assisted with bi-directional switches per-phase), the proposed topology has the capability to regulate voltage from no-load to full load. Moreover, the Total Harmonic Distortion (THD) analysis for output (stator) current shows a 9% improvement compared with the most recent results in the literature.
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