plr_remove_outliers: Filter outliers from Power Predicted Data

In PVplr: Performance Loss Rate Analysis Pipeline

Filter outliers from Power Predicted Data

Description

This function is used to remove outliers (if desired) after putting data through a power predictive model, e.g. plr_xbx_model.

Usage

plr_remove_outliers(data)

Arguments

data	A resulting dataframe from a power predictive model.

Value

Returns dataframe with outliers flagged by other functions removed

Examples

# build var_list
var_list <- plr_build_var_list(time_var = "timestamp",
                               power_var = "power",
                               irrad_var = "g_poa",
                               temp_var = "mod_temp",
                               wind_var = NA)
# Clean Data
test_dfc <- plr_cleaning(test_df, var_list, irrad_thresh = 100,
                         low_power_thresh = 0.01, high_power_cutoff = NA)
                         
# Perform the power predictive modeling step
test_xbx_wbw_res <- plr_xbx_model(test_dfc, var_list, by = "week",
                                  data_cutoff = 30, predict_data = NULL)

# Remove outliers from the modeled data
test_xbx_wbw_res_no_outliers <- plr_remove_outliers(test_xbx_wbw_res)

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