Enhanced Efficiencies for High-Concentration, Multijunction PV Systems by Optimizing Grid Spacing under Nonuniform Illumination
Bibliographic record
Abstract
The design of a triple junction solar cell’s front contact grid can significantly affect cell conversion efficiency under high concentration. We consider one aspect of grid design, choosing a linear grid within a distributed resistance cell model to optimize finger spacings at concentrations between 500 and 2500 suns under uniform and nonuniform illumination. Optimization for maximum efficiency under Gaussian irradiance profiles is done by SPICE analysis. Relative to the optimized uniform illumination designs, we find enhancements of 0.5% to 2% in absolute efficiencies for uniform spacing. Efficiency enhancement with nonuniform spacing under nonuniform illumination is also evaluated. Our model suggests that, at lower concentrations (<1000 suns), the penalty for using uniformly spaced fingers instead of nonuniformly spaced fingers is <0.1%. However, at a concentration of 2500 suns the penalty increases to 0.3%. Thus, relative to a uniform irradiance optimization, an absolute efficiency increase of 2.3% can be attained for an optimized nonuniform spacing given the Gaussian irradiance profile under consideration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".