In timchurches/SPProKit: What the Package Does (One Line, Title Case)

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library(tidyverse)

csv_path <- "~/Documents/Chatham_Valley/Solar/SPLINK/Waligada/"
csv_files <- c("PerformanceData_2021-12-16_10-01-47/Waligada_DetailedData_2021-12-16_10-01-47.CSV",
               "PerformanceData_2021-12-17_15-22-39/Waligada_DetailedData_2021-12-17_15-22-39.CSV",
               "PerformanceData_2021-12-18_08-41-26/Waligada_DetailedData_2021-12-18_08-41-26.CSV",
               "PerformanceData_2021-12-19_14-53-35/Waligada_DetailedData_2021-12-19_14-53-35.CSV",
               "PerformanceData_2021-12-20_09-07-49/Waligada_DetailedData_2021-12-20_09-07-49.CSV")

if (exists("waligada")) rm(waligada)
if (exists("csv_data")) rm(csv_data)

for (f in csv_files) {               
    csv_data <- readr::read_csv(paste0(csv_path,f))
    if (exists("waligada")) {
        waligada <- waligada %>%
            bind_rows(csv_data)
    } else {
        waligada <- csv_data
    }
}    

Parameter_order <- c(
                "SoC %",            
                "Avg AC load (kW)",         
                "Log avg AC load (log kW)",
                "Max AC load (kW)",         
                "Log max AC load (log kW)",         
                "Avg DC (V)",           
                "Avg inverter AC power (kW)",           
                "Avg inverter DC current (A)",          
                "Cum AC load (kWh)",            
                "Cum AC coupled energy in (kWh)",           
                "Total AC coupled power in (kW)",
                "Cum bat in (kWh)",         
                "Cum bat out (kWh)",            
                "Cum DC input (kWh)",           
                "Cum DC output (kWh)")          

waligada <- waligada %>%
    janitor::clean_names() %>%
    mutate(date_time = clock::date_time_parse(date_time_stamp_dd_mm_yyyy_hh_mm_ss, "Australia/Sydney", format="%d/%m/%Y - %H:%M:%S")) %>%
    mutate(log_load_ac_power_average_k_w = log10(load_ac_power_average_k_w),
           log_load_ac_power_max_k_w = log10(load_ac_power_max_k_w)) %>%
    select(date_time, 
           state_of_charge_sample_percent,
           dc_voltage_average_v_dc,
           # dc_voltage_max_v_dc,
           # dc_voltage_min_v_dc,
           dc_input_accumulated_sample_k_wh,
           dc_output_accumulated_sample_k_wh,
           battery_in_accumulated_sample_k_wh,
           battery_out_accumulated_sample_k_wh,
           load_ac_power_average_k_w,
           log_load_ac_power_average_k_w,
           load_ac_power_max_k_w,
           log_load_ac_power_max_k_w,
           ac_load_k_wh_accumulated_sample_k_wh,
           total_ac_coupled_power_average_k_w,
           total_ac_coupled_energy_sample_k_wh,
           inverter_ac_power_average_k_w,
           inverter_dc_current_average_a
           ) %>%
    rename("SoC %"=state_of_charge_sample_percent,
           "Avg DC (V)" = dc_voltage_average_v_dc,
           # "Max DC V" = dc_voltage_max_v_dc,
           # "Min DC V" = dc_voltage_min_v_dc,
           "Cum DC input (kWh)" = dc_input_accumulated_sample_k_wh,
           "Cum DC output (kWh)" = dc_output_accumulated_sample_k_wh,
           "Cum bat in (kWh)" = battery_in_accumulated_sample_k_wh,
           "Cum bat out (kWh)" = battery_out_accumulated_sample_k_wh,
           "Avg AC load (kW)" = load_ac_power_average_k_w,
           "Log avg AC load (log kW)" = log_load_ac_power_average_k_w,
           "Max AC load (kW)" = load_ac_power_max_k_w,
           "Log max AC load (log kW)" = log_load_ac_power_max_k_w,
           "Cum AC load (kWh)" = ac_load_k_wh_accumulated_sample_k_wh,
           "Total AC coupled power in (kW)" = total_ac_coupled_power_average_k_w,
           "Cum AC coupled energy in (kWh)" = total_ac_coupled_energy_sample_k_wh,
           "Avg inverter AC power (kW)"=inverter_ac_power_average_k_w,
           "Avg inverter DC current (A)"=inverter_dc_current_average_a
           ) %>%
    pivot_longer(!date_time,
                 names_to = "Parameter", 
                 values_to = "Value") %>%
    mutate(Parameter = factor(Parameter,levels=Parameter_order))


#prefmt <- waligada %>% count(Parameter)

#postfmt <- waligada %>%
#    count(Parameter)

#prefmt %>% full_join(postfmt,by = "Parameter")

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tz <- "Australia/Sydney"

waligada %>%
    # filter(date_time >= clock::date_time_build(year=2021, month=12, day = 17, hour = 12, minute = 0, zone=tz),
    #        date_time < clock::date_time_build(year=2021, month=12, day = 17, hour = 14, minute = 0, zone=tz)) %>%
    ggplot(aes(x=date_time, y=Value)) +
               geom_line() +
                labs(x="Date/time") +
                facet_grid(rows = vars(Parameter), 
                           scales = "free_y",
                           labeller = label_wrap_gen(width=6))

tz <- "Australia/Sydney"
x_axis_origin <- clock::date_time_build(year=2021, month=12, day = 12, hour = 4, minute = 0, zone=tz)

waligada %>%
    #filter(date_time >= clock::date_time_build(year=2021, month=12, day = 17, hour = 6, minute = 0, zone=tz),
    #    date_time < clock::date_time_build(year=2021, month=12, day = 17, hour = 18, minute = 0, zone=tz)) %>%
    ggplot(aes(x=date_time, y=Value)) +
               geom_line() +
                scale_x_datetime(name="Date/time",
                                 date_labels = "%a, %d %b %Y %H:%M",
                                 date_breaks = "6 hours",
                                 limits=c(x_axis_origin, NA)) +
                theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
                facet_grid(rows = vars(Parameter), 
                           scales = "free_y",
                           labeller = label_wrap_gen(width=6))

timchurches/SPProKit documentation built on Jan. 16, 2022, 11:23 a.m.