Nothing
R/pof_transformer_30_60kv.R
In CNAIM: Common Network Asset Indices Methodology (CNAIM)
Defines functions
pof_transformer_30_60kv
Documented in
pof_transformer_30_60kv
#' @importFrom magrittr %>%
#' @title Current Probability of Failure for 30/10kV and 60/10kV Transformers
#' @description This function calculates the current
#' annual probability of failure for 30/10kV and 60/10kV transformers.
#' The function is a cubic curve that is based on
#' the first three terms of the Taylor series for an
#' exponential function.
#' @param placement String. Specify if the asset is located outdoor or indoor.
#' @param altitude_m Numeric. Specify the altitude location for
#' the asset measured in meters from sea level.\code{altitude_m}
#' is used to derive the altitude factor. A setting of \code{"Default"}
#' will set the altitude factor to 1 independent of \code{asset_type}.
#' @param distance_from_coast_km Numeric. Specify the distance from the
#' coast measured in kilometers. \code{distance_from_coast_km} is used
#' to derive the distance from coast factor. A setting of \code{"Default"} will set the
#' distance from coast factor to 1 independent of \code{asset_type}.
#' @param transformer_type String. A sting that refers to the specific
#' asset category.
#' Options:
#' \code{transformer_type =
#' c("30kV Transformer (GM)", "60kV Transformer (GM)")}. The default setting is
#' \code{transformer_type = "60kV Transformer (GM)"}
#' @param year_of_manufacture Numeric. Normal expected life depends on the
#' year for manufacture.
#' @inheritParams duty_factor_transformer_33_66kv
#' @inheritParams location_factor
#' @inheritParams current_health
#' @param age_tf Numeric. The current age in years
#' of the transformer.
#' @param age_tc Numeric. The current age in years
#' of the tapchanger
#' @param partial_discharge_tf String. Indicating the
#' level of partial discharge in the transformer.
#' Options:
#' \code{partial_discharge_tf = c("Low", "Medium", "High (Not Confirmed)",
#' "High (Confirmed)", "Default")}.
#' @param partial_discharge_tc String. Indicating the
#' level of partial discharge in the tapchanger
#' Options:
#' \code{partial_discharge_tc = c("Low", "Medium", "High (Not Confirmed)",
#' "High (Confirmed)", "Default")}.
#' @param temperature_reading String. Indicating the criticality.
#' Options:
#' \code{temperature_reading = c("Normal", "Moderately High",
#' "Very High", "Default")}.
#' @param main_tank String. Indicating the observed condition of the
#' main tank. Options:
#' \code{main_tank = c("Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' in CNAIM (2021).
#' @param coolers_radiator String. Indicating the observed condition of the
#' coolers/radiators. Options:
#' \code{coolers_radiator = c("Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' in CNAIM (2021).
#' @param bushings String. Indicating the observed condition of the
#' bushings. Options:
#' \code{bushings = c("Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' @param kiosk String. Indicating the observed condition of the
#' kiosk. Options:
#' \code{kiosk = c("Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' @param cable_boxes String. Indicating the observed condition of the
#' cable boxes. Options:
#' \code{cable_boxes = c("No Deterioration","Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' @param external_tap String. Indicating the observed external condition of the
#' tapchanger. Options:
#' \code{external_tap = c("Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' in CNAIM (2021).
#' @param internal_tap String. Indicating the observed internal condition of the
#' tapchanger. Options:
#' \code{external_tap = c("Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' in CNAIM (2021).
#' @param mechnism_cond String. Indicating the observed condition of the
#' drive mechnism. Options:
#' \code{mechnism_cond = c("No deterioration", "Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' in CNAIM (2021).
#' @param diverter_contacts String. Indicating the observed condition of the
#' selector and diverter contacts. Options:
#' \code{diverter_contacts = c("No deterioration", "Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' in CNAIM (2021).
#' @param diverter_braids String. Indicating the observed condition of the
#' selector and diverter braids. Options:
#' \code{diverter_braids = c("No deterioration", "Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' @param corrosion_category_index Integer.
#' Specify the corrosion index category, 1-5.
#' @param moisture Numeric. the amount of moisture given in (ppm) See page 162, table 203 in CNAIM (2021).
#' @param acidity Numeric. the amount of acidicy given in (mg KOH/g) See page 162, table 204 in CNAIM (2021).
#' @param bd_strength Numeric. the amount of breakdown strength given in (kV) See page 162, table 205 in CNAIM (2021).
#' @param k_value Numeric. \code{k_value = "0.0454"} by default. This number is
#' given in a percentage. The default value is accordingly to the CNAIM standard
#' on p. 110.
#' @param c_value Numeric. \code{c_value = 1.087} by default.
#' The default value is accordingly to the CNAIM standard see page 110
#' @param normal_expected_life_tf Numeric. \code{normal_expected_life_tf = "Default"} by default.
#' The default value is accordingly to the CNAIM standard on page 107.
#' @param normal_expected_life_tc Numeric. \code{normal_expected_life_tc = "Default"} by default.
#' The default value is accordingly to the CNAIM standard on page 107.
#' @inheritParams oil_test_modifier
#' @inheritParams dga_test_modifier
#' @inheritParams ffa_test_modifier
#' @return DataFrame Current probability of failure
#' per annum per kilometer along with current health score.
#' @export
#' @examples
#' # Current probability of failure for a 60/10kV transformer
#' pof_transformer_30_60kv(transformer_type = "60kV Transformer (GM)",
#' year_of_manufacture = 1980,
#' utilisation_pct = "Default",
#' no_taps = "Default",
#' placement = "Default",
#' altitude_m = "Default",
#' distance_from_coast_km = "Default",
#' corrosion_category_index = "Default",
#' age_tf = 43,
#' age_tc = 43,
#' partial_discharge_tf = "Default",
#' partial_discharge_tc = "Default",
#' temperature_reading = "Default",
#' main_tank = "Default",
#' coolers_radiator = "Default",
#' bushings = "Default",
#' kiosk = "Default",
#' cable_boxes = "Default",
#' external_tap = "Default",
#' internal_tap = "Default",
#' mechnism_cond = "Default",
#' diverter_contacts = "Default",
#' diverter_braids = "Default",
#' moisture = "Default",
#' acidity = "Default",
#' bd_strength = "Default",
#' hydrogen = "Default",
#' methane = "Default",
#' ethylene = "Default",
#' ethane = "Default",
#' acetylene = "Default",
#' hydrogen_pre = "Default",
#' methane_pre = "Default",
#' ethylene_pre = "Default",
#' ethane_pre = "Default",
#' acetylene_pre = "Default",
#' furfuraldehyde = "Default",
#' reliability_factor = "Default",
#' k_value = 0.454,
#' c_value = 1.087,
#' normal_expected_life_tf = "Default",
#' normal_expected_life_tc = "Default")
pof_transformer_30_60kv <- function(transformer_type = "60kV Transformer (GM)",
year_of_manufacture,
utilisation_pct = "Default",
no_taps = "Default",
placement = "Default",
altitude_m = "Default",
distance_from_coast_km = "Default",
corrosion_category_index = "Default",
age_tf,
age_tc,
partial_discharge_tf = "Default",
partial_discharge_tc = "Default",
temperature_reading = "Default",
main_tank = "Default",
coolers_radiator = "Default",
bushings = "Default",
kiosk = "Default",
cable_boxes = "Default",
external_tap = "Default",
internal_tap = "Default",
mechnism_cond = "Default",
diverter_contacts = "Default",
diverter_braids = "Default",
moisture = "Default",
acidity = "Default",
bd_strength = "Default",
hydrogen = "Default",
methane = "Default",
ethylene = "Default",
ethane = "Default",
acetylene = "Default",
hydrogen_pre = "Default",
methane_pre = "Default",
ethylene_pre = "Default",
ethane_pre = "Default",
acetylene_pre = "Default",
furfuraldehyde = "Default",
reliability_factor = "Default",
k_value = 0.454,
c_value = 1.087,
normal_expected_life_tf = "Default",
normal_expected_life_tc = "Default") {
if (transformer_type == "30kV Transformer (GM)" ) {
transformer_type <- "33kV Transformer (GM)"
} else {
transformer_type <- "66kV Transformer (GM)"
}
`Asset Register Category` = `Health Index Asset Category` =
`Generic Term...1` = `Generic Term...2` = `Functional Failure Category` =
`K-Value (%)` = `C-Value` = `Asset Register Category` = `Sub-division` =
`Asset Category` = NULL
# due to NSE notes in R CMD check
# Ref. table Categorisation of Assets and Generic Terms for Assets --
asset_category <- gb_ref$categorisation_of_assets %>%
dplyr::filter(`Asset Register Category` == transformer_type) %>%
dplyr::select(`Health Index Asset Category`) %>% dplyr::pull()
generic_term_1 <- gb_ref$generic_terms_for_assets %>%
dplyr::filter(`Health Index Asset Category` == asset_category) %>%
dplyr::select(`Generic Term...1`) %>% dplyr::pull()
generic_term_2 <- gb_ref$generic_terms_for_assets %>%
dplyr::filter(`Health Index Asset Category` == asset_category) %>%
dplyr::select(`Generic Term...2`) %>% dplyr::pull()
# Normal expected life for transformer -----------------------------
if (year_of_manufacture < 1980) {
sub_division <- "Transformer - Pre 1980"
} else {
sub_division <- "Transformer - Post 1980"
}
if (normal_expected_life_tf == "Default") {
normal_expected_life_tf <- gb_ref$normal_expected_life %>%
dplyr::filter(`Asset Register Category` == transformer_type & `Sub-division` ==
sub_division) %>%
dplyr::pull()
} else {
normal_expected_life_tf <- normal_expected_life_tf
}
# Normal expected life for tapchanger -----------------------------
if (normal_expected_life_tc == "Default") {
normal_expected_life_tc <- gb_ref$normal_expected_life %>%
dplyr::filter(`Asset Register Category` == transformer_type & `Sub-division` ==
"Tapchanger") %>%
dplyr::pull()
} else {
normal_expected_life_tc <- normal_expected_life_tc
}
# Constants C and K for PoF function --------------------------------------
k <- k_value/100
c <- c_value
# Duty factor -------------------------------------------------------------
duty_factor_tf_11kv <- duty_factor_transformer_33_66kv(utilisation_pct,
no_taps)
duty_factor_tf <-
duty_factor_tf_11kv$duty_factor[which(duty_factor_tf_11kv$category ==
"transformer")]
duty_factor_tc <-
duty_factor_tf_11kv$duty_factor[which(duty_factor_tf_11kv$category ==
"tapchanger")]
# Location factor ----------------------------------------------------
location_factor_transformer <- location_factor(placement,
altitude_m,
distance_from_coast_km,
corrosion_category_index,
asset_type = transformer_type)
# Expected life for transformer ------------------------------
expected_life_years_tf <- expected_life(normal_expected_life =
normal_expected_life_tf,
duty_factor_tf,
location_factor_transformer)
# Expected life for tapchanger ------------------------------
expected_life_years_tc <- expected_life(normal_expected_life =
normal_expected_life_tc,
duty_factor_tc,
location_factor_transformer)
# b1 (Initial Ageing Rate) ------------------------------------------------
b1_tf <- beta_1(expected_life_years_tf)
b1_tc <- beta_1(expected_life_years_tc)
# Initial health score ----------------------------------------------------
initial_health_score_tf <- initial_health(b1_tf, age_tf)
initial_health_score_tc <- initial_health(b1_tc, age_tc)
## NOTE
# Typically, the Health Score Collar is 0.5 and
# Health Score Cap is 10, implying no overriding
# of the Health Score. However, in some instances
# these parameters are set to other values in the
# Health Score Modifier calibration tables.
# Measured condition inputs ---------------------------------------------
mcm_mmi_cal_df <-
gb_ref$measured_cond_modifier_mmi_cal
mcm_mmi_cal_df <-
mcm_mmi_cal_df[which(mcm_mmi_cal_df$`Asset Category` == "EHV Transformer (GM)"), ]
factor_divider_1_tf <-
as.numeric(mcm_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 1`[
which(mcm_mmi_cal_df$Subcomponent == "Main Transformer")
])
factor_divider_1_tc <-
as.numeric(mcm_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 1`[
which(mcm_mmi_cal_df$Subcomponent == "Tapchanger")
])
factor_divider_2_tf <-
as.numeric(mcm_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 2`[
which(mcm_mmi_cal_df$Subcomponent == "Main Transformer")
])
factor_divider_2_tc <-
as.numeric(mcm_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 2`[
which(mcm_mmi_cal_df$Subcomponent == "Tapchanger")
])
max_no_combined_factors_tf <-
as.numeric(mcm_mmi_cal_df$`Parameters for Combination Using MMI Technique - Max. No. of Combined Factors`[
which(mcm_mmi_cal_df$Subcomponent == "Main Transformer")
])
max_no_combined_factors_tc <-
as.numeric(mcm_mmi_cal_df$`Parameters for Combination Using MMI Technique - Max. No. of Combined Factors`[
which(mcm_mmi_cal_df$Subcomponent == "Tapchanger")
])
# Partial discharge transformer ----------------------------------------------
mci_hv_tf_partial_discharge <-
gb_ref$mci_ehv_tf_main_tf_prtl_dis
ci_factor_partial_discharge_tf <-
mci_hv_tf_partial_discharge$`Condition Input Factor`[which(
mci_hv_tf_partial_discharge$
`Condition Criteria: Partial Discharge Test Result` ==
partial_discharge_tf)]
ci_cap_partial_discharge_tf <-
mci_hv_tf_partial_discharge$`Condition Input Cap`[which(
mci_hv_tf_partial_discharge$
`Condition Criteria: Partial Discharge Test Result` ==
partial_discharge_tf)]
ci_collar_partial_discharge_tf <-
mci_hv_tf_partial_discharge$`Condition Input Collar`[which(
mci_hv_tf_partial_discharge$
`Condition Criteria: Partial Discharge Test Result` ==
partial_discharge_tf)]
# Partial discharge tapchanger ------------------------------------------------
mci_hv_tf_partial_discharge_tc <-
gb_ref$mci_ehv_tf_tapchngr_prtl_dis
ci_factor_partial_discharge_tc <-
mci_hv_tf_partial_discharge_tc$`Condition Input Factor`[which(
mci_hv_tf_partial_discharge_tc$
`Condition Criteria: Partial Discharge Test Result` ==
partial_discharge_tc)]
ci_cap_partial_discharge_tc <-
mci_hv_tf_partial_discharge_tc$`Condition Input Cap`[which(
mci_hv_tf_partial_discharge_tc$
`Condition Criteria: Partial Discharge Test Result` ==
partial_discharge_tc)]
ci_collar_partial_discharge_tc <-
mci_hv_tf_partial_discharge_tc$`Condition Input Collar`[which(
mci_hv_tf_partial_discharge_tc$
`Condition Criteria: Partial Discharge Test Result` ==
partial_discharge_tc)]
# Temperature readings ----------------------------------------------------
mci_hv_tf_temp_readings <-
gb_ref$mci_ehv_tf_temp_readings
ci_factor_temp_reading <-
mci_hv_tf_temp_readings$`Condition Input Factor`[which(
mci_hv_tf_temp_readings$
`Condition Criteria: Temperature Reading` ==
temperature_reading)]
ci_cap_temp_reading <-
mci_hv_tf_temp_readings$`Condition Input Cap`[which(
mci_hv_tf_temp_readings$
`Condition Criteria: Temperature Reading` ==
temperature_reading)]
ci_collar_temp_reading <-
mci_hv_tf_temp_readings$`Condition Input Collar`[which(
mci_hv_tf_temp_readings$
`Condition Criteria: Temperature Reading` ==
temperature_reading)]
# measured condition factor -----------------------------------------------
factors_tf <- c(ci_factor_partial_discharge_tf,
ci_factor_temp_reading)
measured_condition_factor_tf <- mmi(factors_tf,
factor_divider_1_tf,
factor_divider_2_tf,
max_no_combined_factors_tf)
measured_condition_factor_tc <- mmi(ci_factor_partial_discharge_tc,
factor_divider_1_tc,
factor_divider_2_tc,
max_no_combined_factors_tc)
# Measured condition cap --------------------------------------------------
caps_tf <- c(ci_cap_partial_discharge_tf,
ci_cap_temp_reading)
measured_condition_cap_tf <- min(caps_tf)
measured_condition_cap_tc <- ci_cap_partial_discharge_tc
# Measured condition collar -----------------------------------------------
collars_tf <- c(ci_collar_partial_discharge_tf,
ci_collar_temp_reading)
measured_condition_collar_tf <- max(collars_tf)
measured_condition_collar_tc <- ci_collar_partial_discharge_tc
# Measured condition modifier ---------------------------------------------
measured_condition_modifier_tf <- data.frame(measured_condition_factor_tf,
measured_condition_cap_tf,
measured_condition_collar_tf)
measured_condition_modifier_tc <- data.frame(measured_condition_factor_tc,
measured_condition_cap_tc,
measured_condition_collar_tc)
# Observed condition inputs ---------------------------------------------
oci_mmi_cal_df <-
gb_ref$observed_cond_modifier_mmi_cal %>%
dplyr::filter(`Asset Category` == "EHV Transformer (GM)")
factor_divider_1_tf_obs <-
as.numeric(oci_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 1`[
which(oci_mmi_cal_df$Subcomponent ==
"Main Transformer") ])
factor_divider_1_tc_obs <-
as.numeric(oci_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 1`[
which(oci_mmi_cal_df$Subcomponent ==
"Tapchanger") ])
factor_divider_2_tf_obs <-
as.numeric(oci_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 2`[
which(oci_mmi_cal_df$Subcomponent ==
"Main Transformer") ])
factor_divider_2_tc_obs <-
as.numeric(oci_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 2`[
which(oci_mmi_cal_df$Subcomponent ==
"Tapchanger") ])
max_no_combined_factors_tf_obs <-
as.numeric(oci_mmi_cal_df$`Parameters for Combination Using MMI Technique - Max. No. of Combined Factors`[
which(oci_mmi_cal_df$Subcomponent ==
"Main Transformer") ])
max_no_combined_factors_tc_obs <-
as.numeric(oci_mmi_cal_df$`Parameters for Combination Using MMI Technique - Max. No. of Combined Factors`[
which(oci_mmi_cal_df$Subcomponent ==
"Tapchanger") ])
# Transformer -------------------------------------------------------------
# Main tank condition
oci_ehv_tf_main_tank_cond <-
gb_ref$oci_ehv_tf_main_tank_cond
Oi_collar_main_tank <-
oci_ehv_tf_main_tank_cond$`Condition Input Collar`[which(
oci_ehv_tf_main_tank_cond$`Condition Criteria: Observed Condition` ==
main_tank)]
Oi_cap_main_tank <-
oci_ehv_tf_main_tank_cond$`Condition Input Cap`[which(
oci_ehv_tf_main_tank_cond$`Condition Criteria: Observed Condition` ==
main_tank)]
Oi_factor_main_tank <-
oci_ehv_tf_main_tank_cond$`Condition Input Factor`[which(
oci_ehv_tf_main_tank_cond$`Condition Criteria: Observed Condition` ==
main_tank)]
# Coolers/Radiator condition
oci_ehv_tf_cooler_radiatr_cond <-
gb_ref$oci_ehv_tf_cooler_radiatr_cond
Oi_collar_coolers_radiator <-
oci_ehv_tf_cooler_radiatr_cond$`Condition Input Collar`[which(
oci_ehv_tf_cooler_radiatr_cond$`Condition Criteria: Observed Condition` ==
coolers_radiator)]
Oi_cap_coolers_radiator <-
oci_ehv_tf_cooler_radiatr_cond$`Condition Input Cap`[which(
oci_ehv_tf_cooler_radiatr_cond$`Condition Criteria: Observed Condition` ==
coolers_radiator)]
Oi_factor_coolers_radiator <-
oci_ehv_tf_cooler_radiatr_cond$`Condition Input Factor`[which(
oci_ehv_tf_cooler_radiatr_cond$`Condition Criteria: Observed Condition` ==
coolers_radiator)]
# Bushings
oci_ehv_tf_bushings_cond <-
gb_ref$oci_ehv_tf_bushings_cond
Oi_collar_bushings <-
oci_ehv_tf_bushings_cond$`Condition Input Collar`[which(
oci_ehv_tf_bushings_cond$`Condition Criteria: Observed Condition` ==
bushings)]
Oi_cap_bushings <-
oci_ehv_tf_bushings_cond$`Condition Input Cap`[which(
oci_ehv_tf_bushings_cond$`Condition Criteria: Observed Condition` ==
bushings)]
Oi_factor_bushings <-
oci_ehv_tf_bushings_cond$`Condition Input Factor`[which(
oci_ehv_tf_bushings_cond$`Condition Criteria: Observed Condition` ==
bushings)]
# Kiosk
oci_ehv_tf_kiosk_cond <-
gb_ref$oci_ehv_tf_kiosk_cond
Oi_collar_kiosk <-
oci_ehv_tf_kiosk_cond$`Condition Input Collar`[which(
oci_ehv_tf_kiosk_cond$`Condition Criteria: Observed Condition` ==
kiosk)]
Oi_cap_kiosk <-
oci_ehv_tf_kiosk_cond$`Condition Input Cap`[which(
oci_ehv_tf_kiosk_cond$`Condition Criteria: Observed Condition` ==
kiosk)]
Oi_factor_kiosk <-
oci_ehv_tf_kiosk_cond$`Condition Input Factor`[which(
oci_ehv_tf_kiosk_cond$`Condition Criteria: Observed Condition` ==
kiosk)]
# Cable box
oci_ehv_tf_cable_boxes_cond <-
gb_ref$oci_ehv_tf_cable_boxes_cond
Oi_collar_cable_boxes <-
oci_ehv_tf_cable_boxes_cond$`Condition Input Collar`[which(
oci_ehv_tf_cable_boxes_cond$`Condition Criteria: Observed Condition` ==
cable_boxes)]
Oi_cap_cable_boxes <-
oci_ehv_tf_cable_boxes_cond$`Condition Input Cap`[which(
oci_ehv_tf_cable_boxes_cond$`Condition Criteria: Observed Condition` ==
cable_boxes)]
Oi_factor_cable_boxes <-
oci_ehv_tf_cable_boxes_cond$`Condition Input Factor`[which(
oci_ehv_tf_cable_boxes_cond$`Condition Criteria: Observed Condition` ==
cable_boxes)]
# Tapchanger --------------------------------------------------------------
# External condition
oci_ehv_tf_tapchanger_ext_cond <-
gb_ref$oci_ehv_tf_tapchanger_ext_cond
Oi_collar_external_tap <-
oci_ehv_tf_tapchanger_ext_cond$`Condition Input Collar`[which(
oci_ehv_tf_tapchanger_ext_cond$`Condition Criteria: Observed Condition` ==
external_tap)]
Oi_cap_external_tap <-
oci_ehv_tf_tapchanger_ext_cond$`Condition Input Cap`[which(
oci_ehv_tf_tapchanger_ext_cond$`Condition Criteria: Observed Condition` ==
external_tap)]
Oi_factor_external_tap <-
oci_ehv_tf_tapchanger_ext_cond$`Condition Input Factor`[which(
oci_ehv_tf_tapchanger_ext_cond$`Condition Criteria: Observed Condition` ==
external_tap)]
# Internal condition
oci_ehv_tf_int_cond <-
gb_ref$oci_ehv_tf_int_cond
Oi_collar_internal_tap <-
oci_ehv_tf_int_cond$`Condition Input Collar`[which(
oci_ehv_tf_int_cond$`Condition Criteria: Observed Condition` ==
internal_tap)]
Oi_cap_internal_tap <-
oci_ehv_tf_int_cond$`Condition Input Cap`[which(
oci_ehv_tf_int_cond$`Condition Criteria: Observed Condition` ==
internal_tap)]
Oi_factor_internal_tap <-
oci_ehv_tf_int_cond$`Condition Input Factor`[which(
oci_ehv_tf_int_cond$`Condition Criteria: Observed Condition` ==
internal_tap)]
# Drive mechanism
oci_ehv_tf_drive_mechnism_cond <-
gb_ref$oci_ehv_tf_drive_mechnism_cond
Oi_collar_mechnism_cond <-
oci_ehv_tf_drive_mechnism_cond$`Condition Input Collar`[which(
oci_ehv_tf_drive_mechnism_cond$`Condition Criteria: Observed Condition` ==
mechnism_cond)]
Oi_cap_mechnism_cond <-
oci_ehv_tf_drive_mechnism_cond$`Condition Input Cap`[which(
oci_ehv_tf_drive_mechnism_cond$`Condition Criteria: Observed Condition` ==
mechnism_cond)]
Oi_factor_mechnism_cond <-
oci_ehv_tf_drive_mechnism_cond$`Condition Input Factor`[which(
oci_ehv_tf_drive_mechnism_cond$`Condition Criteria: Observed Condition` ==
mechnism_cond)]
# Selecter diverter contacts
oci_ehv_tf_cond_select_divrter_cst <-
gb_ref$oci_ehv_tf_cond_select_div_cts
Oi_collar_diverter_contacts <-
oci_ehv_tf_cond_select_divrter_cst$`Condition Input Collar`[which(
oci_ehv_tf_cond_select_divrter_cst$`Condition Criteria: Observed Condition` ==
diverter_contacts)]
Oi_cap_diverter_contacts <-
oci_ehv_tf_cond_select_divrter_cst$`Condition Input Cap`[which(
oci_ehv_tf_cond_select_divrter_cst$`Condition Criteria: Observed Condition` ==
diverter_contacts)]
Oi_factor_diverter_contacts <-
oci_ehv_tf_cond_select_divrter_cst$`Condition Input Factor`[which(
oci_ehv_tf_cond_select_divrter_cst$`Condition Criteria: Observed Condition` ==
diverter_contacts)]
# Selecter diverter braids
oci_ehv_tf_cond_select_divrter_brd <-
gb_ref$oci_ehv_tf_cond_select_div_brd
Oi_collar_diverter_braids <-
oci_ehv_tf_cond_select_divrter_brd$`Condition Input Collar`[which(
oci_ehv_tf_cond_select_divrter_brd$`Condition Criteria: Observed Condition` ==
diverter_braids)]
Oi_cap_diverter_braids <-
oci_ehv_tf_cond_select_divrter_brd$`Condition Input Cap`[which(
oci_ehv_tf_cond_select_divrter_brd$`Condition Criteria: Observed Condition` ==
diverter_braids)]
Oi_factor_diverter_braids <-
oci_ehv_tf_cond_select_divrter_brd$`Condition Input Factor`[which(
oci_ehv_tf_cond_select_divrter_brd$`Condition Criteria: Observed Condition` ==
diverter_braids)]
# Observed condition factor --------------------------------------
# Transformer
factors_tf_obs <- c(Oi_factor_main_tank,
Oi_factor_coolers_radiator,
Oi_factor_bushings,
Oi_factor_kiosk,
Oi_factor_cable_boxes)
observed_condition_factor_tf <- mmi(factors_tf_obs,
factor_divider_1_tf_obs,
factor_divider_2_tf_obs,
max_no_combined_factors_tf_obs)
# Tapchanger
factors_tc_obs <- c(Oi_factor_external_tap,
Oi_factor_internal_tap,
Oi_factor_mechnism_cond,
Oi_factor_diverter_contacts,
Oi_factor_diverter_braids)
observed_condition_factor_tc <- mmi(factors_tc_obs,
factor_divider_1_tc_obs,
factor_divider_2_tc_obs,
max_no_combined_factors_tc_obs)
# Observed condition cap -----------------------------------------
# Transformer
caps_tf_obs <- c(Oi_cap_main_tank,
Oi_cap_coolers_radiator,
Oi_cap_bushings,
Oi_cap_kiosk,
Oi_cap_cable_boxes)
observed_condition_cap_tf <- min(caps_tf_obs)
# Tapchanger
caps_tc_obs <- c(Oi_cap_external_tap,
Oi_cap_internal_tap,
Oi_cap_mechnism_cond,
Oi_cap_diverter_contacts,
Oi_cap_diverter_braids)
observed_condition_cap_tc <- min(caps_tc_obs)
# Observed condition collar ---------------------------------------
# Transformer
collars_tf_obs <- c(Oi_collar_main_tank,
Oi_collar_coolers_radiator,
Oi_collar_bushings,
Oi_collar_kiosk,
Oi_collar_cable_boxes)
observed_condition_collar_tf <- max(collars_tf_obs)
# Tapchanger
collars_tc_obs <- c(Oi_collar_external_tap,
Oi_collar_internal_tap,
Oi_collar_mechnism_cond,
Oi_collar_diverter_contacts,
Oi_collar_diverter_braids)
observed_condition_collar_tc <- max(collars_tc_obs)
# Observed condition modifier ---------------------------------------------
# Transformer
observed_condition_modifier_tf <- data.frame(observed_condition_factor_tf,
observed_condition_cap_tf,
observed_condition_collar_tf)
# Tapchanger
observed_condition_modifier_tc <- data.frame(observed_condition_factor_tc,
observed_condition_cap_tc,
observed_condition_collar_tc)
# Oil test modifier -------------------------------------------------------
oil_test_mod <- oil_test_modifier(moisture,
acidity,
bd_strength)
# DGA test modifier -------------------------------------------------------
dga_test_mod <- dga_test_modifier(hydrogen,
methane,
ethylene,
ethane,
acetylene,
hydrogen_pre,
methane_pre,
ethylene_pre,
ethane_pre,
acetylene_pre)
# FFA test modifier -------------------------------------------------------
ffa_test_mod <- ffa_test_modifier(furfuraldehyde)
# Health score factor ---------------------------------------------------
health_score_factor_for_tf <- gb_ref$health_score_factor_for_tf
health_score_factor_tapchanger <- gb_ref$health_score_factor_tapchanger
# Transformer
factor_divider_1_tf_health <-
health_score_factor_for_tf$`Parameters for Combination Using MMI Technique - Factor Divider 1`
factor_divider_2_tf_health <-
health_score_factor_for_tf$`Parameters for Combination Using MMI Technique - Factor Divider 2`
max_no_combined_factors_tf_health <-
health_score_factor_for_tf$`Parameters for Combination Using MMI Technique - Max. No. of Condition Factors`
# Tapchanger
factor_divider_1_tc_health <-
health_score_factor_tapchanger$`Parameters for Combination Using MMI Technique - Factor Divider 1`
factor_divider_2_tc_health <-
health_score_factor_tapchanger$`Parameters for Combination Using MMI Technique - Factor Divider 2`
max_no_combined_factors_tc_health <-
health_score_factor_tapchanger$`Parameters for Combination Using MMI Technique - Max. No. of Condition Factors`
# Health score modifier -----------------------------------------------------
# Transformer
obs_tf_factor <- observed_condition_modifier_tf$observed_condition_factor_tf
mea_tf_factor <- measured_condition_modifier_tf$measured_condition_factor_tf
oil_factor <- oil_test_mod$oil_condition_factor
dga_factor <- dga_test_mod$dga_test_factor
ffa_factor <- ffa_test_mod$ffa_test_factor
factors_tf_health <- c(obs_tf_factor,
mea_tf_factor,
oil_factor,
dga_factor,
ffa_factor)
health_score_factor_tf <- mmi(factors_tf_health,
factor_divider_1_tf_health,
factor_divider_2_tf_health,
max_no_combined_factors_tf_health)
# tapchanger
obs_tc_factor <- observed_condition_modifier_tc$observed_condition_factor_tc
mea_tc_factor <- measured_condition_modifier_tc$measured_condition_factor_tc
factors_tc_health <- c(obs_tc_factor,
mea_tc_factor,
oil_factor)
health_score_factor_tc <- mmi(factors_tc_health,
factor_divider_1_tc_health,
factor_divider_2_tc_health,
max_no_combined_factors_tc_health)
# Health score cap --------------------------------------------------------
# Transformer
health_score_cap_tf <- min(observed_condition_modifier_tf$observed_condition_cap_tf,
measured_condition_modifier_tf$measured_condition_cap_tf,
oil_test_mod$oil_condition_cap,
dga_test_mod$dga_test_cap,
ffa_test_mod$ffa_test_cap)
# Tapchanger
health_score_cap_tc <- min(observed_condition_modifier_tc$observed_condition_cap_tc,
measured_condition_modifier_tc$measured_condition_cap_tc,
oil_test_mod$oil_condition_cap)
# Health score collar -----------------------------------------------------
# Transformer
health_score_collar_tf <- max(observed_condition_modifier_tf$observed_condition_collar_tf,
measured_condition_modifier_tf$measured_condition_collar_tf,
oil_test_mod$oil_condition_collar,
dga_test_mod$dga_test_collar,
ffa_test_mod$ffa_test_collar)
# Tapchanger
health_score_collar_tc <- max(observed_condition_modifier_tc$observed_condition_collar_tc,
measured_condition_modifier_tc$measured_condition_collar_tc,
oil_test_mod$oil_condition_collar)
# Health score modifier ---------------------------------------------------
# transformer
health_score_modifier_tf <- data.frame(health_score_factor_tf,
health_score_cap_tf,
health_score_collar_tf)
# Tapchanger
health_score_modifier_tc <- data.frame(health_score_factor_tc,
health_score_cap_tc,
health_score_collar_tc)
# Current health score ----------------------------------------------------
# Transformer
current_health_score <-
max(current_health(initial_health_score_tf,
health_score_modifier_tf$health_score_factor_tf,
health_score_modifier_tf$health_score_cap_tf,
health_score_modifier_tf$health_score_collar,
reliability_factor = reliability_factor),
current_health(initial_health_score_tf,
health_score_modifier_tc$health_score_factor_tc,
health_score_modifier_tc$health_score_cap_tc,
health_score_modifier_tc$health_score_collar_tc,
reliability_factor = reliability_factor))
# Probability of failure for the 6.6/11 kV transformer today -----------------
probability_of_failure <- k *
(1 + (c * current_health_score) +
(((c * current_health_score)^2) / factorial(2)) +
(((c * current_health_score)^3) / factorial(3)))
return(data.frame(pof = probability_of_failure, chs = current_health_score))
}
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Defines functions pof_transformer_30_60kv
Documented in pof_transformer_30_60kv
#' @importFrom magrittr %>%
#' @title Current Probability of Failure for 30/10kV and 60/10kV Transformers
#' @description This function calculates the current
#' annual probability of failure for 30/10kV and 60/10kV transformers.
#' The function is a cubic curve that is based on
#' the first three terms of the Taylor series for an
#' exponential function.
#' @param placement String. Specify if the asset is located outdoor or indoor.
#' @param altitude_m Numeric. Specify the altitude location for
#' the asset measured in meters from sea level.\code{altitude_m}
#' is used to derive the altitude factor. A setting of \code{"Default"}
#' will set the altitude factor to 1 independent of \code{asset_type}.
#' @param distance_from_coast_km Numeric. Specify the distance from the
#' coast measured in kilometers. \code{distance_from_coast_km} is used
#' to derive the distance from coast factor. A setting of \code{"Default"} will set the
#' distance from coast factor to 1 independent of \code{asset_type}.
#' @param transformer_type String. A sting that refers to the specific
#' asset category.
#' Options:
#' \code{transformer_type =
#' c("30kV Transformer (GM)", "60kV Transformer (GM)")}. The default setting is
#' \code{transformer_type = "60kV Transformer (GM)"}
#' @param year_of_manufacture Numeric. Normal expected life depends on the
#' year for manufacture.
#' @inheritParams duty_factor_transformer_33_66kv
#' @inheritParams location_factor
#' @inheritParams current_health
#' @param age_tf Numeric. The current age in years
#' of the transformer.
#' @param age_tc Numeric. The current age in years
#' of the tapchanger
#' @param partial_discharge_tf String. Indicating the
#' level of partial discharge in the transformer.
#' Options:
#' \code{partial_discharge_tf = c("Low", "Medium", "High (Not Confirmed)",
#' "High (Confirmed)", "Default")}.
#' @param partial_discharge_tc String. Indicating the
#' level of partial discharge in the tapchanger
#' Options:
#' \code{partial_discharge_tc = c("Low", "Medium", "High (Not Confirmed)",
#' "High (Confirmed)", "Default")}.
#' @param temperature_reading String. Indicating the criticality.
#' Options:
#' \code{temperature_reading = c("Normal", "Moderately High",
#' "Very High", "Default")}.
#' @param main_tank String. Indicating the observed condition of the
#' main tank. Options:
#' \code{main_tank = c("Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' in CNAIM (2021).
#' @param coolers_radiator String. Indicating the observed condition of the
#' coolers/radiators. Options:
#' \code{coolers_radiator = c("Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' in CNAIM (2021).
#' @param bushings String. Indicating the observed condition of the
#' bushings. Options:
#' \code{bushings = c("Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' @param kiosk String. Indicating the observed condition of the
#' kiosk. Options:
#' \code{kiosk = c("Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' @param cable_boxes String. Indicating the observed condition of the
#' cable boxes. Options:
#' \code{cable_boxes = c("No Deterioration","Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' @param external_tap String. Indicating the observed external condition of the
#' tapchanger. Options:
#' \code{external_tap = c("Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' in CNAIM (2021).
#' @param internal_tap String. Indicating the observed internal condition of the
#' tapchanger. Options:
#' \code{external_tap = c("Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' in CNAIM (2021).
#' @param mechnism_cond String. Indicating the observed condition of the
#' drive mechnism. Options:
#' \code{mechnism_cond = c("No deterioration", "Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' in CNAIM (2021).
#' @param diverter_contacts String. Indicating the observed condition of the
#' selector and diverter contacts. Options:
#' \code{diverter_contacts = c("No deterioration", "Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' in CNAIM (2021).
#' @param diverter_braids String. Indicating the observed condition of the
#' selector and diverter braids. Options:
#' \code{diverter_braids = c("No deterioration", "Superficial/minor deterioration", "Some Deterioration",
#' "Substantial Deterioration", "Default")}.
#' @param corrosion_category_index Integer.
#' Specify the corrosion index category, 1-5.
#' @param moisture Numeric. the amount of moisture given in (ppm) See page 162, table 203 in CNAIM (2021).
#' @param acidity Numeric. the amount of acidicy given in (mg KOH/g) See page 162, table 204 in CNAIM (2021).
#' @param bd_strength Numeric. the amount of breakdown strength given in (kV) See page 162, table 205 in CNAIM (2021).
#' @param k_value Numeric. \code{k_value = "0.0454"} by default. This number is
#' given in a percentage. The default value is accordingly to the CNAIM standard
#' on p. 110.
#' @param c_value Numeric. \code{c_value = 1.087} by default.
#' The default value is accordingly to the CNAIM standard see page 110
#' @param normal_expected_life_tf Numeric. \code{normal_expected_life_tf = "Default"} by default.
#' The default value is accordingly to the CNAIM standard on page 107.
#' @param normal_expected_life_tc Numeric. \code{normal_expected_life_tc = "Default"} by default.
#' The default value is accordingly to the CNAIM standard on page 107.
#' @inheritParams oil_test_modifier
#' @inheritParams dga_test_modifier
#' @inheritParams ffa_test_modifier
#' @return DataFrame Current probability of failure
#' per annum per kilometer along with current health score.
#' @export
#' @examples
#' # Current probability of failure for a 60/10kV transformer
#' pof_transformer_30_60kv(transformer_type = "60kV Transformer (GM)",
#' year_of_manufacture = 1980,
#' utilisation_pct = "Default",
#' no_taps = "Default",
#' placement = "Default",
#' altitude_m = "Default",
#' distance_from_coast_km = "Default",
#' corrosion_category_index = "Default",
#' age_tf = 43,
#' age_tc = 43,
#' partial_discharge_tf = "Default",
#' partial_discharge_tc = "Default",
#' temperature_reading = "Default",
#' main_tank = "Default",
#' coolers_radiator = "Default",
#' bushings = "Default",
#' kiosk = "Default",
#' cable_boxes = "Default",
#' external_tap = "Default",
#' internal_tap = "Default",
#' mechnism_cond = "Default",
#' diverter_contacts = "Default",
#' diverter_braids = "Default",
#' moisture = "Default",
#' acidity = "Default",
#' bd_strength = "Default",
#' hydrogen = "Default",
#' methane = "Default",
#' ethylene = "Default",
#' ethane = "Default",
#' acetylene = "Default",
#' hydrogen_pre = "Default",
#' methane_pre = "Default",
#' ethylene_pre = "Default",
#' ethane_pre = "Default",
#' acetylene_pre = "Default",
#' furfuraldehyde = "Default",
#' reliability_factor = "Default",
#' k_value = 0.454,
#' c_value = 1.087,
#' normal_expected_life_tf = "Default",
#' normal_expected_life_tc = "Default")
pof_transformer_30_60kv <- function(transformer_type = "60kV Transformer (GM)",
year_of_manufacture,
utilisation_pct = "Default",
no_taps = "Default",
placement = "Default",
altitude_m = "Default",
distance_from_coast_km = "Default",
corrosion_category_index = "Default",
age_tf,
age_tc,
partial_discharge_tf = "Default",
partial_discharge_tc = "Default",
temperature_reading = "Default",
main_tank = "Default",
coolers_radiator = "Default",
bushings = "Default",
kiosk = "Default",
cable_boxes = "Default",
external_tap = "Default",
internal_tap = "Default",
mechnism_cond = "Default",
diverter_contacts = "Default",
diverter_braids = "Default",
moisture = "Default",
acidity = "Default",
bd_strength = "Default",
hydrogen = "Default",
methane = "Default",
ethylene = "Default",
ethane = "Default",
acetylene = "Default",
hydrogen_pre = "Default",
methane_pre = "Default",
ethylene_pre = "Default",
ethane_pre = "Default",
acetylene_pre = "Default",
furfuraldehyde = "Default",
reliability_factor = "Default",
k_value = 0.454,
c_value = 1.087,
normal_expected_life_tf = "Default",
normal_expected_life_tc = "Default") {
if (transformer_type == "30kV Transformer (GM)" ) {
transformer_type <- "33kV Transformer (GM)"
} else {
transformer_type <- "66kV Transformer (GM)"
}
`Asset Register Category` = `Health Index Asset Category` =
`Generic Term...1` = `Generic Term...2` = `Functional Failure Category` =
`K-Value (%)` = `C-Value` = `Asset Register Category` = `Sub-division` =
`Asset Category` = NULL
# due to NSE notes in R CMD check
# Ref. table Categorisation of Assets and Generic Terms for Assets --
asset_category <- gb_ref$categorisation_of_assets %>%
dplyr::filter(`Asset Register Category` == transformer_type) %>%
dplyr::select(`Health Index Asset Category`) %>% dplyr::pull()
generic_term_1 <- gb_ref$generic_terms_for_assets %>%
dplyr::filter(`Health Index Asset Category` == asset_category) %>%
dplyr::select(`Generic Term...1`) %>% dplyr::pull()
generic_term_2 <- gb_ref$generic_terms_for_assets %>%
dplyr::filter(`Health Index Asset Category` == asset_category) %>%
dplyr::select(`Generic Term...2`) %>% dplyr::pull()
# Normal expected life for transformer -----------------------------
if (year_of_manufacture < 1980) {
sub_division <- "Transformer - Pre 1980"
} else {
sub_division <- "Transformer - Post 1980"
}
if (normal_expected_life_tf == "Default") {
normal_expected_life_tf <- gb_ref$normal_expected_life %>%
dplyr::filter(`Asset Register Category` == transformer_type & `Sub-division` ==
sub_division) %>%
dplyr::pull()
} else {
normal_expected_life_tf <- normal_expected_life_tf
}
# Normal expected life for tapchanger -----------------------------
if (normal_expected_life_tc == "Default") {
normal_expected_life_tc <- gb_ref$normal_expected_life %>%
dplyr::filter(`Asset Register Category` == transformer_type & `Sub-division` ==
"Tapchanger") %>%
dplyr::pull()
} else {
normal_expected_life_tc <- normal_expected_life_tc
}
# Constants C and K for PoF function --------------------------------------
k <- k_value/100
c <- c_value
# Duty factor -------------------------------------------------------------
duty_factor_tf_11kv <- duty_factor_transformer_33_66kv(utilisation_pct,
no_taps)
duty_factor_tf <-
duty_factor_tf_11kv$duty_factor[which(duty_factor_tf_11kv$category ==
"transformer")]
duty_factor_tc <-
duty_factor_tf_11kv$duty_factor[which(duty_factor_tf_11kv$category ==
"tapchanger")]
# Location factor ----------------------------------------------------
location_factor_transformer <- location_factor(placement,
altitude_m,
distance_from_coast_km,
corrosion_category_index,
asset_type = transformer_type)
# Expected life for transformer ------------------------------
expected_life_years_tf <- expected_life(normal_expected_life =
normal_expected_life_tf,
duty_factor_tf,
location_factor_transformer)
# Expected life for tapchanger ------------------------------
expected_life_years_tc <- expected_life(normal_expected_life =
normal_expected_life_tc,
duty_factor_tc,
location_factor_transformer)
# b1 (Initial Ageing Rate) ------------------------------------------------
b1_tf <- beta_1(expected_life_years_tf)
b1_tc <- beta_1(expected_life_years_tc)
# Initial health score ----------------------------------------------------
initial_health_score_tf <- initial_health(b1_tf, age_tf)
initial_health_score_tc <- initial_health(b1_tc, age_tc)
## NOTE
# Typically, the Health Score Collar is 0.5 and
# Health Score Cap is 10, implying no overriding
# of the Health Score. However, in some instances
# these parameters are set to other values in the
# Health Score Modifier calibration tables.
# Measured condition inputs ---------------------------------------------
mcm_mmi_cal_df <-
gb_ref$measured_cond_modifier_mmi_cal
mcm_mmi_cal_df <-
mcm_mmi_cal_df[which(mcm_mmi_cal_df$`Asset Category` == "EHV Transformer (GM)"), ]
factor_divider_1_tf <-
as.numeric(mcm_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 1`[
which(mcm_mmi_cal_df$Subcomponent == "Main Transformer")
])
factor_divider_1_tc <-
as.numeric(mcm_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 1`[
which(mcm_mmi_cal_df$Subcomponent == "Tapchanger")
])
factor_divider_2_tf <-
as.numeric(mcm_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 2`[
which(mcm_mmi_cal_df$Subcomponent == "Main Transformer")
])
factor_divider_2_tc <-
as.numeric(mcm_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 2`[
which(mcm_mmi_cal_df$Subcomponent == "Tapchanger")
])
max_no_combined_factors_tf <-
as.numeric(mcm_mmi_cal_df$`Parameters for Combination Using MMI Technique - Max. No. of Combined Factors`[
which(mcm_mmi_cal_df$Subcomponent == "Main Transformer")
])
max_no_combined_factors_tc <-
as.numeric(mcm_mmi_cal_df$`Parameters for Combination Using MMI Technique - Max. No. of Combined Factors`[
which(mcm_mmi_cal_df$Subcomponent == "Tapchanger")
])
# Partial discharge transformer ----------------------------------------------
mci_hv_tf_partial_discharge <-
gb_ref$mci_ehv_tf_main_tf_prtl_dis
ci_factor_partial_discharge_tf <-
mci_hv_tf_partial_discharge$`Condition Input Factor`[which(
mci_hv_tf_partial_discharge$
`Condition Criteria: Partial Discharge Test Result` ==
partial_discharge_tf)]
ci_cap_partial_discharge_tf <-
mci_hv_tf_partial_discharge$`Condition Input Cap`[which(
mci_hv_tf_partial_discharge$
`Condition Criteria: Partial Discharge Test Result` ==
partial_discharge_tf)]
ci_collar_partial_discharge_tf <-
mci_hv_tf_partial_discharge$`Condition Input Collar`[which(
mci_hv_tf_partial_discharge$
`Condition Criteria: Partial Discharge Test Result` ==
partial_discharge_tf)]
# Partial discharge tapchanger ------------------------------------------------
mci_hv_tf_partial_discharge_tc <-
gb_ref$mci_ehv_tf_tapchngr_prtl_dis
ci_factor_partial_discharge_tc <-
mci_hv_tf_partial_discharge_tc$`Condition Input Factor`[which(
mci_hv_tf_partial_discharge_tc$
`Condition Criteria: Partial Discharge Test Result` ==
partial_discharge_tc)]
ci_cap_partial_discharge_tc <-
mci_hv_tf_partial_discharge_tc$`Condition Input Cap`[which(
mci_hv_tf_partial_discharge_tc$
`Condition Criteria: Partial Discharge Test Result` ==
partial_discharge_tc)]
ci_collar_partial_discharge_tc <-
mci_hv_tf_partial_discharge_tc$`Condition Input Collar`[which(
mci_hv_tf_partial_discharge_tc$
`Condition Criteria: Partial Discharge Test Result` ==
partial_discharge_tc)]
# Temperature readings ----------------------------------------------------
mci_hv_tf_temp_readings <-
gb_ref$mci_ehv_tf_temp_readings
ci_factor_temp_reading <-
mci_hv_tf_temp_readings$`Condition Input Factor`[which(
mci_hv_tf_temp_readings$
`Condition Criteria: Temperature Reading` ==
temperature_reading)]
ci_cap_temp_reading <-
mci_hv_tf_temp_readings$`Condition Input Cap`[which(
mci_hv_tf_temp_readings$
`Condition Criteria: Temperature Reading` ==
temperature_reading)]
ci_collar_temp_reading <-
mci_hv_tf_temp_readings$`Condition Input Collar`[which(
mci_hv_tf_temp_readings$
`Condition Criteria: Temperature Reading` ==
temperature_reading)]
# measured condition factor -----------------------------------------------
factors_tf <- c(ci_factor_partial_discharge_tf,
ci_factor_temp_reading)
measured_condition_factor_tf <- mmi(factors_tf,
factor_divider_1_tf,
factor_divider_2_tf,
max_no_combined_factors_tf)
measured_condition_factor_tc <- mmi(ci_factor_partial_discharge_tc,
factor_divider_1_tc,
factor_divider_2_tc,
max_no_combined_factors_tc)
# Measured condition cap --------------------------------------------------
caps_tf <- c(ci_cap_partial_discharge_tf,
ci_cap_temp_reading)
measured_condition_cap_tf <- min(caps_tf)
measured_condition_cap_tc <- ci_cap_partial_discharge_tc
# Measured condition collar -----------------------------------------------
collars_tf <- c(ci_collar_partial_discharge_tf,
ci_collar_temp_reading)
measured_condition_collar_tf <- max(collars_tf)
measured_condition_collar_tc <- ci_collar_partial_discharge_tc
# Measured condition modifier ---------------------------------------------
measured_condition_modifier_tf <- data.frame(measured_condition_factor_tf,
measured_condition_cap_tf,
measured_condition_collar_tf)
measured_condition_modifier_tc <- data.frame(measured_condition_factor_tc,
measured_condition_cap_tc,
measured_condition_collar_tc)
# Observed condition inputs ---------------------------------------------
oci_mmi_cal_df <-
gb_ref$observed_cond_modifier_mmi_cal %>%
dplyr::filter(`Asset Category` == "EHV Transformer (GM)")
factor_divider_1_tf_obs <-
as.numeric(oci_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 1`[
which(oci_mmi_cal_df$Subcomponent ==
"Main Transformer") ])
factor_divider_1_tc_obs <-
as.numeric(oci_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 1`[
which(oci_mmi_cal_df$Subcomponent ==
"Tapchanger") ])
factor_divider_2_tf_obs <-
as.numeric(oci_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 2`[
which(oci_mmi_cal_df$Subcomponent ==
"Main Transformer") ])
factor_divider_2_tc_obs <-
as.numeric(oci_mmi_cal_df$`Parameters for Combination Using MMI Technique - Factor Divider 2`[
which(oci_mmi_cal_df$Subcomponent ==
"Tapchanger") ])
max_no_combined_factors_tf_obs <-
as.numeric(oci_mmi_cal_df$`Parameters for Combination Using MMI Technique - Max. No. of Combined Factors`[
which(oci_mmi_cal_df$Subcomponent ==
"Main Transformer") ])
max_no_combined_factors_tc_obs <-
as.numeric(oci_mmi_cal_df$`Parameters for Combination Using MMI Technique - Max. No. of Combined Factors`[
which(oci_mmi_cal_df$Subcomponent ==
"Tapchanger") ])
# Transformer -------------------------------------------------------------
# Main tank condition
oci_ehv_tf_main_tank_cond <-
gb_ref$oci_ehv_tf_main_tank_cond
Oi_collar_main_tank <-
oci_ehv_tf_main_tank_cond$`Condition Input Collar`[which(
oci_ehv_tf_main_tank_cond$`Condition Criteria: Observed Condition` ==
main_tank)]
Oi_cap_main_tank <-
oci_ehv_tf_main_tank_cond$`Condition Input Cap`[which(
oci_ehv_tf_main_tank_cond$`Condition Criteria: Observed Condition` ==
main_tank)]
Oi_factor_main_tank <-
oci_ehv_tf_main_tank_cond$`Condition Input Factor`[which(
oci_ehv_tf_main_tank_cond$`Condition Criteria: Observed Condition` ==
main_tank)]
# Coolers/Radiator condition
oci_ehv_tf_cooler_radiatr_cond <-
gb_ref$oci_ehv_tf_cooler_radiatr_cond
Oi_collar_coolers_radiator <-
oci_ehv_tf_cooler_radiatr_cond$`Condition Input Collar`[which(
oci_ehv_tf_cooler_radiatr_cond$`Condition Criteria: Observed Condition` ==
coolers_radiator)]
Oi_cap_coolers_radiator <-
oci_ehv_tf_cooler_radiatr_cond$`Condition Input Cap`[which(
oci_ehv_tf_cooler_radiatr_cond$`Condition Criteria: Observed Condition` ==
coolers_radiator)]
Oi_factor_coolers_radiator <-
oci_ehv_tf_cooler_radiatr_cond$`Condition Input Factor`[which(
oci_ehv_tf_cooler_radiatr_cond$`Condition Criteria: Observed Condition` ==
coolers_radiator)]
# Bushings
oci_ehv_tf_bushings_cond <-
gb_ref$oci_ehv_tf_bushings_cond
Oi_collar_bushings <-
oci_ehv_tf_bushings_cond$`Condition Input Collar`[which(
oci_ehv_tf_bushings_cond$`Condition Criteria: Observed Condition` ==
bushings)]
Oi_cap_bushings <-
oci_ehv_tf_bushings_cond$`Condition Input Cap`[which(
oci_ehv_tf_bushings_cond$`Condition Criteria: Observed Condition` ==
bushings)]
Oi_factor_bushings <-
oci_ehv_tf_bushings_cond$`Condition Input Factor`[which(
oci_ehv_tf_bushings_cond$`Condition Criteria: Observed Condition` ==
bushings)]
# Kiosk
oci_ehv_tf_kiosk_cond <-
gb_ref$oci_ehv_tf_kiosk_cond
Oi_collar_kiosk <-
oci_ehv_tf_kiosk_cond$`Condition Input Collar`[which(
oci_ehv_tf_kiosk_cond$`Condition Criteria: Observed Condition` ==
kiosk)]
Oi_cap_kiosk <-
oci_ehv_tf_kiosk_cond$`Condition Input Cap`[which(
oci_ehv_tf_kiosk_cond$`Condition Criteria: Observed Condition` ==
kiosk)]
Oi_factor_kiosk <-
oci_ehv_tf_kiosk_cond$`Condition Input Factor`[which(
oci_ehv_tf_kiosk_cond$`Condition Criteria: Observed Condition` ==
kiosk)]
# Cable box
oci_ehv_tf_cable_boxes_cond <-
gb_ref$oci_ehv_tf_cable_boxes_cond
Oi_collar_cable_boxes <-
oci_ehv_tf_cable_boxes_cond$`Condition Input Collar`[which(
oci_ehv_tf_cable_boxes_cond$`Condition Criteria: Observed Condition` ==
cable_boxes)]
Oi_cap_cable_boxes <-
oci_ehv_tf_cable_boxes_cond$`Condition Input Cap`[which(
oci_ehv_tf_cable_boxes_cond$`Condition Criteria: Observed Condition` ==
cable_boxes)]
Oi_factor_cable_boxes <-
oci_ehv_tf_cable_boxes_cond$`Condition Input Factor`[which(
oci_ehv_tf_cable_boxes_cond$`Condition Criteria: Observed Condition` ==
cable_boxes)]
# Tapchanger --------------------------------------------------------------
# External condition
oci_ehv_tf_tapchanger_ext_cond <-
gb_ref$oci_ehv_tf_tapchanger_ext_cond
Oi_collar_external_tap <-
oci_ehv_tf_tapchanger_ext_cond$`Condition Input Collar`[which(
oci_ehv_tf_tapchanger_ext_cond$`Condition Criteria: Observed Condition` ==
external_tap)]
Oi_cap_external_tap <-
oci_ehv_tf_tapchanger_ext_cond$`Condition Input Cap`[which(
oci_ehv_tf_tapchanger_ext_cond$`Condition Criteria: Observed Condition` ==
external_tap)]
Oi_factor_external_tap <-
oci_ehv_tf_tapchanger_ext_cond$`Condition Input Factor`[which(
oci_ehv_tf_tapchanger_ext_cond$`Condition Criteria: Observed Condition` ==
external_tap)]
# Internal condition
oci_ehv_tf_int_cond <-
gb_ref$oci_ehv_tf_int_cond
Oi_collar_internal_tap <-
oci_ehv_tf_int_cond$`Condition Input Collar`[which(
oci_ehv_tf_int_cond$`Condition Criteria: Observed Condition` ==
internal_tap)]
Oi_cap_internal_tap <-
oci_ehv_tf_int_cond$`Condition Input Cap`[which(
oci_ehv_tf_int_cond$`Condition Criteria: Observed Condition` ==
internal_tap)]
Oi_factor_internal_tap <-
oci_ehv_tf_int_cond$`Condition Input Factor`[which(
oci_ehv_tf_int_cond$`Condition Criteria: Observed Condition` ==
internal_tap)]
# Drive mechanism
oci_ehv_tf_drive_mechnism_cond <-
gb_ref$oci_ehv_tf_drive_mechnism_cond
Oi_collar_mechnism_cond <-
oci_ehv_tf_drive_mechnism_cond$`Condition Input Collar`[which(
oci_ehv_tf_drive_mechnism_cond$`Condition Criteria: Observed Condition` ==
mechnism_cond)]
Oi_cap_mechnism_cond <-
oci_ehv_tf_drive_mechnism_cond$`Condition Input Cap`[which(
oci_ehv_tf_drive_mechnism_cond$`Condition Criteria: Observed Condition` ==
mechnism_cond)]
Oi_factor_mechnism_cond <-
oci_ehv_tf_drive_mechnism_cond$`Condition Input Factor`[which(
oci_ehv_tf_drive_mechnism_cond$`Condition Criteria: Observed Condition` ==
mechnism_cond)]
# Selecter diverter contacts
oci_ehv_tf_cond_select_divrter_cst <-
gb_ref$oci_ehv_tf_cond_select_div_cts
Oi_collar_diverter_contacts <-
oci_ehv_tf_cond_select_divrter_cst$`Condition Input Collar`[which(
oci_ehv_tf_cond_select_divrter_cst$`Condition Criteria: Observed Condition` ==
diverter_contacts)]
Oi_cap_diverter_contacts <-
oci_ehv_tf_cond_select_divrter_cst$`Condition Input Cap`[which(
oci_ehv_tf_cond_select_divrter_cst$`Condition Criteria: Observed Condition` ==
diverter_contacts)]
Oi_factor_diverter_contacts <-
oci_ehv_tf_cond_select_divrter_cst$`Condition Input Factor`[which(
oci_ehv_tf_cond_select_divrter_cst$`Condition Criteria: Observed Condition` ==
diverter_contacts)]
# Selecter diverter braids
oci_ehv_tf_cond_select_divrter_brd <-
gb_ref$oci_ehv_tf_cond_select_div_brd
Oi_collar_diverter_braids <-
oci_ehv_tf_cond_select_divrter_brd$`Condition Input Collar`[which(
oci_ehv_tf_cond_select_divrter_brd$`Condition Criteria: Observed Condition` ==
diverter_braids)]
Oi_cap_diverter_braids <-
oci_ehv_tf_cond_select_divrter_brd$`Condition Input Cap`[which(
oci_ehv_tf_cond_select_divrter_brd$`Condition Criteria: Observed Condition` ==
diverter_braids)]
Oi_factor_diverter_braids <-
oci_ehv_tf_cond_select_divrter_brd$`Condition Input Factor`[which(
oci_ehv_tf_cond_select_divrter_brd$`Condition Criteria: Observed Condition` ==
diverter_braids)]
# Observed condition factor --------------------------------------
# Transformer
factors_tf_obs <- c(Oi_factor_main_tank,
Oi_factor_coolers_radiator,
Oi_factor_bushings,
Oi_factor_kiosk,
Oi_factor_cable_boxes)
observed_condition_factor_tf <- mmi(factors_tf_obs,
factor_divider_1_tf_obs,
factor_divider_2_tf_obs,
max_no_combined_factors_tf_obs)
# Tapchanger
factors_tc_obs <- c(Oi_factor_external_tap,
Oi_factor_internal_tap,
Oi_factor_mechnism_cond,
Oi_factor_diverter_contacts,
Oi_factor_diverter_braids)
observed_condition_factor_tc <- mmi(factors_tc_obs,
factor_divider_1_tc_obs,
factor_divider_2_tc_obs,
max_no_combined_factors_tc_obs)
# Observed condition cap -----------------------------------------
# Transformer
caps_tf_obs <- c(Oi_cap_main_tank,
Oi_cap_coolers_radiator,
Oi_cap_bushings,
Oi_cap_kiosk,
Oi_cap_cable_boxes)
observed_condition_cap_tf <- min(caps_tf_obs)
# Tapchanger
caps_tc_obs <- c(Oi_cap_external_tap,
Oi_cap_internal_tap,
Oi_cap_mechnism_cond,
Oi_cap_diverter_contacts,
Oi_cap_diverter_braids)
observed_condition_cap_tc <- min(caps_tc_obs)
# Observed condition collar ---------------------------------------
# Transformer
collars_tf_obs <- c(Oi_collar_main_tank,
Oi_collar_coolers_radiator,
Oi_collar_bushings,
Oi_collar_kiosk,
Oi_collar_cable_boxes)
observed_condition_collar_tf <- max(collars_tf_obs)
# Tapchanger
collars_tc_obs <- c(Oi_collar_external_tap,
Oi_collar_internal_tap,
Oi_collar_mechnism_cond,
Oi_collar_diverter_contacts,
Oi_collar_diverter_braids)
observed_condition_collar_tc <- max(collars_tc_obs)
# Observed condition modifier ---------------------------------------------
# Transformer
observed_condition_modifier_tf <- data.frame(observed_condition_factor_tf,
observed_condition_cap_tf,
observed_condition_collar_tf)
# Tapchanger
observed_condition_modifier_tc <- data.frame(observed_condition_factor_tc,
observed_condition_cap_tc,
observed_condition_collar_tc)
# Oil test modifier -------------------------------------------------------
oil_test_mod <- oil_test_modifier(moisture,
acidity,
bd_strength)
# DGA test modifier -------------------------------------------------------
dga_test_mod <- dga_test_modifier(hydrogen,
methane,
ethylene,
ethane,
acetylene,
hydrogen_pre,
methane_pre,
ethylene_pre,
ethane_pre,
acetylene_pre)
# FFA test modifier -------------------------------------------------------
ffa_test_mod <- ffa_test_modifier(furfuraldehyde)
# Health score factor ---------------------------------------------------
health_score_factor_for_tf <- gb_ref$health_score_factor_for_tf
health_score_factor_tapchanger <- gb_ref$health_score_factor_tapchanger
# Transformer
factor_divider_1_tf_health <-
health_score_factor_for_tf$`Parameters for Combination Using MMI Technique - Factor Divider 1`
factor_divider_2_tf_health <-
health_score_factor_for_tf$`Parameters for Combination Using MMI Technique - Factor Divider 2`
max_no_combined_factors_tf_health <-
health_score_factor_for_tf$`Parameters for Combination Using MMI Technique - Max. No. of Condition Factors`
# Tapchanger
factor_divider_1_tc_health <-
health_score_factor_tapchanger$`Parameters for Combination Using MMI Technique - Factor Divider 1`
factor_divider_2_tc_health <-
health_score_factor_tapchanger$`Parameters for Combination Using MMI Technique - Factor Divider 2`
max_no_combined_factors_tc_health <-
health_score_factor_tapchanger$`Parameters for Combination Using MMI Technique - Max. No. of Condition Factors`
# Health score modifier -----------------------------------------------------
# Transformer
obs_tf_factor <- observed_condition_modifier_tf$observed_condition_factor_tf
mea_tf_factor <- measured_condition_modifier_tf$measured_condition_factor_tf
oil_factor <- oil_test_mod$oil_condition_factor
dga_factor <- dga_test_mod$dga_test_factor
ffa_factor <- ffa_test_mod$ffa_test_factor
factors_tf_health <- c(obs_tf_factor,
mea_tf_factor,
oil_factor,
dga_factor,
ffa_factor)
health_score_factor_tf <- mmi(factors_tf_health,
factor_divider_1_tf_health,
factor_divider_2_tf_health,
max_no_combined_factors_tf_health)
# tapchanger
obs_tc_factor <- observed_condition_modifier_tc$observed_condition_factor_tc
mea_tc_factor <- measured_condition_modifier_tc$measured_condition_factor_tc
factors_tc_health <- c(obs_tc_factor,
mea_tc_factor,
oil_factor)
health_score_factor_tc <- mmi(factors_tc_health,
factor_divider_1_tc_health,
factor_divider_2_tc_health,
max_no_combined_factors_tc_health)
# Health score cap --------------------------------------------------------
# Transformer
health_score_cap_tf <- min(observed_condition_modifier_tf$observed_condition_cap_tf,
measured_condition_modifier_tf$measured_condition_cap_tf,
oil_test_mod$oil_condition_cap,
dga_test_mod$dga_test_cap,
ffa_test_mod$ffa_test_cap)
# Tapchanger
health_score_cap_tc <- min(observed_condition_modifier_tc$observed_condition_cap_tc,
measured_condition_modifier_tc$measured_condition_cap_tc,
oil_test_mod$oil_condition_cap)
# Health score collar -----------------------------------------------------
# Transformer
health_score_collar_tf <- max(observed_condition_modifier_tf$observed_condition_collar_tf,
measured_condition_modifier_tf$measured_condition_collar_tf,
oil_test_mod$oil_condition_collar,
dga_test_mod$dga_test_collar,
ffa_test_mod$ffa_test_collar)
# Tapchanger
health_score_collar_tc <- max(observed_condition_modifier_tc$observed_condition_collar_tc,
measured_condition_modifier_tc$measured_condition_collar_tc,
oil_test_mod$oil_condition_collar)
# Health score modifier ---------------------------------------------------
# transformer
health_score_modifier_tf <- data.frame(health_score_factor_tf,
health_score_cap_tf,
health_score_collar_tf)
# Tapchanger
health_score_modifier_tc <- data.frame(health_score_factor_tc,
health_score_cap_tc,
health_score_collar_tc)
# Current health score ----------------------------------------------------
# Transformer
current_health_score <-
max(current_health(initial_health_score_tf,
health_score_modifier_tf$health_score_factor_tf,
health_score_modifier_tf$health_score_cap_tf,
health_score_modifier_tf$health_score_collar,
reliability_factor = reliability_factor),
current_health(initial_health_score_tf,
health_score_modifier_tc$health_score_factor_tc,
health_score_modifier_tc$health_score_cap_tc,
health_score_modifier_tc$health_score_collar_tc,
reliability_factor = reliability_factor))
# Probability of failure for the 6.6/11 kV transformer today -----------------
probability_of_failure <- k *
(1 + (c * current_health_score) +
(((c * current_health_score)^2) / factorial(2)) +
(((c * current_health_score)^3) / factorial(3)))
return(data.frame(pof = probability_of_failure, chs = current_health_score))
}
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