Modular Power-Balanced Resonant Converters for MVdc Distributed PV 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
Research into the use of medium-voltage dc (MVdc) grids is on the rise due to advantages including lower maintenance costs, lower loss, and simpler controllability compared to their ac counterpart. The operating voltage of a typical PV array system is quite low compared to the MVdc level which has led to advances in module-based input independent output series (IIOS) configurations to improve the output voltage level while providing individual maximum power point tracking (MPPT) for each module. Due to varying solar irradiation, atmospheric conditions, and PV manufacturing differences, converter modules will operate at varying power levels leading to modular power mismatch which can result in overvoltage scenarios, damaged components, and ultimately the failure of the system. In this article, a new interconnecting modular full-bridge step-up LLC resonant converter is proposed for IIOS based MVdc PV energy applications. The proposed system’s converter module is capable of regulating power flow between mismatched modules through the use of pulse-width modulation (PWM) control on a new active voltage doubler based voltage balancer (VD). To achieve individual maximum power point tracking (MPPT) in each module, phase-shift control is used on the input full bridge switches of each module. The use of the LLC resonant converter allows for zero-voltage switching operation on all module switches to enhance the system efficiency while stepping up the PV voltage. These configurations allow the modular PV system to achieve simultaneous MPPT, soft-switching operation, and balanced output voltage operation over a wide operating range of PV irradiation levels. The steady-state and dynamic performance of the designed system is validated on a five module 6kW, 12kV-output simulation and a scaled-down 1.6kW, 1.6kV-output two module laboratory prototype.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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