plr_cleaning: Basic Data Cleaning

In PVplr: Performance Loss Rate Analysis Pipeline

Basic Data Cleaning

Description

Removes entries with irradiance and power readings outside cutoffs, fixes timestamps to your specified format, and converts columns to numeric when appropriate - see plr_convert_columns. Also, adds columns for days/weeks/years of operation that are used by other functions.

Usage

plr_cleaning(
  df,
  var_list,
  irrad_thresh = 100,
  low_power_thresh = 0.05,
  high_power_cutoff = NA,
  tmst_format = "%Y-%m-%d %H:%M:%S"
)

Arguments

df	A dataframe containing pv data.
var_list	A list of the dataframe's standard variable names, obtained from the output of plr_variable_check.
irrad_thresh	The lowest meaningful irradiance value. Values below are filtered.
low_power_thresh	The lowest meaningful power output. Values below are filtered.
high_power_cutoff	The highest meaningful power output. Values above are filtered.
tmst_format	The desired timestamp format.

Value

Returns dataframe with rows filtered out based on passed cleaning parameters

Examples

var_list <- plr_build_var_list(time_var = "timestamp",
                               power_var = "power",
                               irrad_var = "g_poa",
                               temp_var = "mod_temp",
                               wind_var = NA)
                               
test_dfc <- plr_cleaning(test_df, var_list, irrad_thresh = 100,
                         low_power_thresh = 0.01, high_power_cutoff = NA)

PVplr documentation built on Feb. 16, 2023, 9:56 p.m.