Package: PVplr 0.1.2
Roger French
PVplr: Performance Loss Rate Analysis Pipeline
The pipeline contained in this package provides tools used in the Solar Durability and Lifetime Extension Center (SDLE) for the analysis of Performance Loss Rates (PLR) in real world photovoltaic systems. Functions included allow for data cleaning, feature correction, power predictive modeling, PLR determination, and uncertainty bootstrapping through various methods <doi:10.1109/PVSC40753.2019.8980928>. The vignette "Pipeline Walkthrough" gives an explicit run through of typical package usage. 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-EE-0008172. This work made use of the High Performance Computing Resource in the Core Facility for Advanced Research Computing at Case Western Reserve University.
Authors:
PVplr_0.1.2.tar.gz
PVplr_0.1.2.zip(r-4.5)PVplr_0.1.2.zip(r-4.4)PVplr_0.1.2.zip(r-4.3)
PVplr_0.1.2.tgz(r-4.4-any)PVplr_0.1.2.tgz(r-4.3-any)
PVplr_0.1.2.tar.gz(r-4.5-noble)PVplr_0.1.2.tar.gz(r-4.4-noble)
PVplr_0.1.2.tgz(r-4.4-emscripten)PVplr_0.1.2.tgz(r-4.3-emscripten)
PVplr.pdf |PVplr.html✨
PVplr/json (API)
# Install 'PVplr' in R: |
install.packages('PVplr', repos = c('https://cwru-sdle.r-universe.dev', 'https://cloud.r-project.org')) |
- test_df - DOE RTC Sample PV System Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:0e746175d0. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 12 2024 |
R-4.5-win | OK | Nov 12 2024 |
R-4.5-linux | OK | Nov 12 2024 |
R-4.4-win | OK | Nov 12 2024 |
R-4.4-mac | OK | Nov 12 2024 |
R-4.3-win | OK | Nov 12 2024 |
R-4.3-mac | OK | Nov 12 2024 |
Exports:all_naanomaly_detectordata_quality_checkdata_structuregrade_pvIntmbm_resamplencnum_testparallel_cluster_exportplr_6k_modelplr_bootstrap_outputplr_bootstrap_output_from_resultsplr_bootstrap_uncertaintyplr_build_var_listplr_cleaningplr_convert_columnsplr_decompositionplr_pvheatmapplr_pvusa_modelplr_remove_outliersplr_saturation_removalplr_seg_extractplr_varplr_variable_checkplr_weighted_regressionplr_xbx_modelplr_xbx_utc_modelplr_yoy_regressionspline_timestamp_synctime_frequency
Dependencies:backportsbroomcliclustercolorspacecpp11curldplyrfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvminpack.lmmunsellnlmennetpillarpkgconfigpurrrquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalessegmentedstlplusstringistringrtibbletidyrtidyselecttimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtsyaImputezoo
Feature Correction
Rendered fromfeature_correction.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2020-10-07
Started: 2020-10-07
Power Predictive Model Comparison
Rendered frommodel_comparison.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2020-10-07
Started: 2020-10-07
Evaluation of Non-Linear PLR
Rendered fromnonlinear_plr.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2020-10-07
Started: 2020-10-07
Pipeline Walkthrough
Rendered frompipeline_walkthrough.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2020-10-07
Started: 2020-10-07