plr_variable_check

The method determines the variable names used by the input dataframe.
 It looks for the following labels:<ul>
<li>power_var &lt;- iacp; if not, sets to idcp</li>
<li>time_var &lt;- tmst; if not ,sets to tutc</li>
<li>irrad_var &lt;- poay; if not, sets to ghir</li>
<li>temp_var &lt;- temp; if not, sets to modt</li>
<li>wind_var &lt;- wspa; if applicable, else NULL</li>
</ul>This function assumes data is in a standard HBase format. If you are using other data
 (as you most likely are) you should use the companion function, <code>plr_build_var_list</code>.

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.

Roger French

PVplr

Performance Loss Rate Analysis Pipeline

Alan Curran

Tyler Burleyson

William Oltjen

Sascha Lindig

David Moser

Solar Durability and Lifetime Extension research center 

plr_variable_check function

<dl><dt>df</dt>
<dd>A dataframe containing pv data.</dd></dl>

Arguments

Define Standard Variable Names — plr_variable_check

<dl>

<dt>df</dt>
<dd>A dataframe containing pv data.</dd>

</dl>

plr_variable_check: Define Standard Variable Names

Description

Usage

Value

Arguments

Examples