Analysis of Performance Parameters of Amorphous Photovoltaic Modules under Different Environmental Conditions
Bibliographic record
Abstract
The effects of temperature and radiation intensity on the performance parameters of amorphous hydrogenated silicon (a-Si:H) photovoltaic module have been investigated. An outdoor experimental setup is installed to carryout a series of I-V curve measurements under different irradiance and temperature conditions for the module. A numerical model which considers the effect of series and shunt resistances is developed to evaluate the different parameters of PV modules. Orthogonal distance regression (ODR) algorithm is adapted for fitting I-V measurements and extracting module parameters from I-V measurements. The values of module parameters, series resistance R s , shunt resistance R sh , diode ideality factor n and reverse saturation current I o determined from I-V measurements at different irradiation intensity and temperature range are in good agreement with the corresponding parameters obtained from the developed numerical model. The module parameters extracted from I-V measurements are employed to calculate the module performance parameters, i.e. open circuit voltage V oc , fill factor FF and module efficiency h at different irradiation intensity and temperature range. Present results indicate that the module parameters have a significant effect on module performance. Also, the behavior of V oc is completely different at higher temperatures. Key words : Amorphous module parameters; Ideality factor; Series resistance; Shunt resistance
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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 | 0.001 |
| 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) | 0.001 | 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".