The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
The Data Driven I-V Feature Extraction is used to extract Current-Voltage (I-V) features from I-V curves. I-V curves indicate the relationship between current and voltage for a solar cell or Photovoltaic (PV) modules. The I-V features such as maximum power point (Pmp), shunt resistance (Rsh), series resistance (Rs),short circuit current (Isc), open circuit voltage (Voc), fill factor (FF), current at maximum power (Imp) and voltage at maximum power(Vmp) contain important information of the performance for PV modules. The traditional method uses the single diode model to model I-V curves and extract I-V features. This package does not use the diode model, but uses data-driven a method which select different linear parts of the I-V curves to extract I-V features. This method also uses a sampling method to calculate uncertainties when extracting I-V features. Also, because of the partially shaded array, "steps" occurs in I-V curves. The "Segmented Regression" method is used to identify steps in I-V curves. This material is based upon work supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under Solar Energy Technologies Office (SETO) Agreement Number DE-EE0007140. Further information can be found in the following paper. [1] Ma, X. et al, 2019. <doi:10.1109/JPHOTOV.2019.2928477>.
Version: | 0.1.1 |
Depends: | R (≥ 3.5.0) |
Imports: | MASS (≥ 0.5-3.0), segmented (≥ 0.5-3.0), qpdf (≥ 1.1) |
Suggests: | rmarkdown, testthat, knitr, tidyr |
Published: | 2021-04-14 |
DOI: | 10.32614/CRAN.package.ddiv |
Author: | Wei-Heng Huang [aut], Xuan Ma [aut], Jiqi Liu [aut], Menghong Wang [ctb], Alan J. Curran [ctb], Justin S. Fada [ctb], Jean-Nicolas Jaubert [ctb], Jing Sun [ctb], Jennifer L. Braid [ctb], Jenny Brynjarsdottir [ctb], Roger H. French [aut, cph], Megan M. Morbitzer [ctb, cre] |
Maintainer: | Megan M. Morbitzer <mmm308 at case.edu> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
CRAN checks: | ddiv results |
Package source: | ddiv_0.1.1.tar.gz |
Windows binaries: | r-devel: ddiv_0.1.1.zip, r-release: ddiv_0.1.1.zip, r-oldrel: ddiv_0.1.1.zip |
macOS binaries: | r-release (arm64): ddiv_0.1.1.tgz, r-oldrel (arm64): ddiv_0.1.1.tgz, r-release (x86_64): ddiv_0.1.1.tgz, r-oldrel (x86_64): ddiv_0.1.1.tgz |
Old sources: | ddiv archive |
Reverse imports: | SunsVoc |
Please use the canonical form https://CRAN.R-project.org/package=ddiv to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.