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#' @title Financial cost of Failure for Relays
#' @description This function calculates financial consequences of failure
#' Financial consequences of failure is used in
#' the derivation of consequences of failure see \code{\link{cof}}().
#' Outputted in DKK.
#' @param access_factor_criteria String. Asses Financial factor criteria for relay
#' setting. Options: \code{access_factor_criteria = c("Type A", "Type B", "Type C")}.
#' @export
#' @examples
#' financial_cof_relay(access_factor_criteria = "Type A")
financial_cof_relay <- function(access_factor_criteria) {
GBP_to_DKK <- 8.71
hv_asset_category <- "6.6/11kV CB (GM) Secondary"
`Asset Register Category` = `Health Index Asset Category` = `Asset Category` = NULL
asset_category <- gb_ref$categorisation_of_assets %>%
dplyr::filter(`Asset Register Category` == hv_asset_category) %>%
dplyr::select(`Health Index Asset Category`) %>% dplyr::pull()
# Reference cost of failure table 16 --------------------------------------
reference_costs_of_failure_tf <- dplyr::filter(gb_ref$reference_costs_of_failure,
`Asset Register Category` ==
hv_asset_category)
# Reference financial cost of failure -------------------------------------
fcost <- reference_costs_of_failure_tf$`Financial - (GBP)`
# Type financial factor ---------------------------------------------------
type_financial_factor <- 1
# Access financial factor -------------------------------------------------
access_financial_factors <- gb_ref$access_factor_swg_tf_asset
access_financial_factors_tf <- dplyr::filter(access_financial_factors,
`Asset Category` ==
"HV Switchgear (GM) - Distribution")
if (access_factor_criteria == "Type A") {
access_finacial_factor <-
access_financial_factors_tf$
`Access Factor: Type A Criteria - Normal Access ( & Default Value)`
}
else if (access_factor_criteria == "Type B") {
access_finacial_factor <-
access_financial_factors_tf$
`Access Factor: Type B Criteria - Constrained Access or Confined Working Space`
}
else if (access_factor_criteria == "Type C") {
access_finacial_factor <-
access_financial_factors_tf$
`Access Factor: Type C Criteria - Underground substation`
}
# Financial consequences factor -------------------------------------------
fc_factor <- type_financial_factor * access_finacial_factor
# Financial consequences of failure ---------------------------------------
return((fc_factor * fcost * GBP_to_DKK)/2)
}
#' @title Safety cost of Failure for Relays
#' @description This function calculates safety consequences of failure.
#'Safety consequences of failure is used in
#' the derivation of consequences of failure see \code{\link{cof}}().
#' Outputted in DKK.
#' @param location_risk String Type Financial factor criteria for 50kV fittings
#' Options: \code{location_risk = c("Low", "Medium", "High")}.
#' The default setting is
#' \code{location_risk = "Medium"}.
#' @param type_risk String. Asses Financial factor criteria for 50kV fittings
#' setting
#' Options: \code{type_risk = c("Low", "Medium", "High")}.
#' The default setting is
#' \code{type_risk = "Medium"}.
#' @return Numeric. Financial consequences of failure for relay
#' @export
#' @examples
#' safety_cof_relay(
#' location_risk = "Default",
#' type_risk = "Default")
safety_cof_relay <- function(location_risk,
type_risk) {
GBP_to_DKK <- 8.71
hv_asset_category <- "6.6/11kV CB (GM) Secondary"
`Asset Register Category` = `Health Index Asset Category` = `Asset Category` = NULL
asset_category <- gb_ref$categorisation_of_assets %>%
dplyr::filter(`Asset Register Category` == hv_asset_category) %>%
dplyr::select(`Health Index Asset Category`) %>% dplyr::pull()
reference_costs_of_failure_tf <- dplyr::filter(gb_ref$reference_costs_of_failure,
`Asset Register Category` ==
hv_asset_category)
# Reference financial cost of failure -------------------------------------
scost <- reference_costs_of_failure_tf$`Safety - (GBP)`
if (location_risk == "Default") location_risk <- "Medium (Default)"
if (location_risk == "Medium") location_risk <- "Medium (Default)"
if (type_risk == "Default") type_risk <- "Medium"
safety_conseq_factor_sg_tf_oh <- gb_ref$safety_conseq_factor_sg_tf_oh
row_no <- which(safety_conseq_factor_sg_tf_oh$
`Safety Consequence Factor - Switchgear, Transformers & Overhead Lines...2` ==
location_risk)
col_no <- grep(type_risk, colnames(safety_conseq_factor_sg_tf_oh))
safety_consequence_factor <- safety_conseq_factor_sg_tf_oh[row_no, col_no]
# Safety consequence of failure -------------------------------------------
safety_cof <- safety_consequence_factor * scost
return((safety_cof * GBP_to_DKK)/2)
}
#' @title Environmental cost of Failure for Relays
#' @description This function calculates environmental consequences of failure.
#' Environmental consequences of failure is used in
#' the derivation of consequences of failure see \code{\link{cof}}().
#' Outputted in DKK.
#' Financial consequences of failure for relay
#' @param type_env_factor String The type environment factor of HV asset category
#' Options: \code{type_env_factor = c("Oil", "SF6", "Neither", "Default")}.
#' @param prox_water Numeric. Specify the proximity to a water course in meters.
#' A setting of \code{"Default"} will result in a proximity factor of 1. Thus
#' assume the proximity to a water course is between 80m and 120m
#' @param bunded String. Options: \code{bunded = c("Yes", "No", "Default")}.
#' A setting of \code{"Default"} will result in a bunding factor of 1.
#' @export
#' @examples
#' environmental_cof_relay(
#' type_env_factor = "Oil",
#' prox_water = 95,
#' bunded = "Yes")
environmental_cof_relay <- function(type_env_factor,
prox_water,
bunded) {
GBP_to_DKK <- 8.71
hv_asset_category <- "6.6/11kV CB (GM) Secondary"
`Asset Register Category` = `Health Index Asset Category` = `Asset Category` =
`Type environment factor` = NULL
asset_category <- gb_ref$categorisation_of_assets %>%
dplyr::filter(`Asset Register Category` == hv_asset_category) %>%
dplyr::select(`Health Index Asset Category`) %>% dplyr::pull()
reference_costs_of_failure_tf <- dplyr::filter(gb_ref$reference_costs_of_failure,
`Asset Register Category` ==
hv_asset_category)
# Reference financial cost of failure -------------------------------------
ecost <- reference_costs_of_failure_tf$`Environmental - (GBP)`
# Type env factor -------------------------------------
asset_type_env_factor <- gb_ref$type_enviromental_factor %>%
dplyr::filter(`Type environment factor` == asset_category)
type_environmental_factor <- asset_type_env_factor[[type_env_factor]]
# Size env factor -------------------------------------
size_environmental_factor <- 1
# Location environmetal factor table 231 ----------------------------------
location_environ_al_factor <- gb_ref$location_environ_al_factor
location_environ_al_factor_tf <- dplyr::filter(location_environ_al_factor,
`Asset Register Category` ==
asset_category)
# Bunded "Yes", "No", "Default" ?
if (bunded == "Default") {
bunding_factor <- 1
} else if (bunded == "Yes") {
bunding_factor <-
location_environ_al_factor_tf$`Bunding Factor: Bunded`
} else if (bunded == "No") {
bunding_factor <-
location_environ_al_factor_tf$`Bunding Factor: Not bunded`
}
# Proximity to water.
if(prox_water == "Default") {
prox_factor <- 1
} else if (prox_water >= 40 && prox_water < 80) {
prox_factor <- location_environ_al_factor_tf$
`Proximity Factor: Close to Water Course (between 40m and 80m)`
} else if (prox_water >= 80 && prox_water < 120) {
prox_factor <- location_environ_al_factor_tf$
`Proximity Factor: Moderately Close to Water Course (between 80m and 120m)`
} else if (prox_water > 120) {
prox_factor <- location_environ_al_factor_tf$
`Proximity Factor: Not Close to Water Course (>120m) or No Oil`
} else if (prox_water < 40) {
prox_factor <- location_environ_al_factor_tf$
`Proximity Factor: Very Close to Water Course (<40m)`
}
# Location environmental factor
location_environmental_factor <- prox_factor * bunding_factor
environmental_consequences_factor <- (type_environmental_factor *
size_environmental_factor *
location_environmental_factor)
# Environmental consequences ----------------------------------------------
environmental_cof <- environmental_consequences_factor * ecost
return((environmental_cof * GBP_to_DKK)/2)
}
#' @title Network cost of Failure for Relays
#' @description This function calculates network cost of failure for Relays
#' Network cost of failure
#' is used in the derivation of consequences of failure see \code{\link{cof}}().
#' Outputted in DKK.
#' @param no_customers Numeric. The number of customers
#' fed by an individual asset.
#' @param kva_per_customer Numeric. If the asset have an exceptionally high
#' demand per customer type in kVA per customer. A setting of \code{"Default"}
#' results in a multiplication factor of 1 (cf. table 18, page 90, CNAIM, 2021).
#' @return Numeric. Network cost of failure.
#' @export
#' @examples
#' network_cof_relay(
#' no_customers = 100, kva_per_customer = 40)
network_cof_relay <- function(no_customers,
kva_per_customer = "Default") {
GBP_to_DKK <- 8.71
hv_asset_category <- "6.6/11kV CB (GM) Secondary"
`Asset Register Category` = `Health Index Asset Category` = `Asset Category` = NULL
asset_category <- gb_ref$categorisation_of_assets %>%
dplyr::filter(`Asset Register Category` == hv_asset_category) %>%
dplyr::select(`Health Index Asset Category`) %>% dplyr::pull()
reference_costs_of_failure_tf <- dplyr::filter(gb_ref$reference_costs_of_failure,
`Asset Register Category` ==
hv_asset_category)
# Reference financial cost of failure -------------------------------------
ncost <- reference_costs_of_failure_tf$`Network Performance - (GBP)`
# Customer factor ---------------------------------------------------------
ref_nw_perf_cost_fail_lv_hv <- gb_ref$ref_nw_perf_cost_fail_lv_hv
ref_nw_perf_cost_fail_lv_hv_tf <- dplyr::filter(ref_nw_perf_cost_fail_lv_hv,
`Asset Category` ==
asset_category)
ref_no_cust <-
ref_nw_perf_cost_fail_lv_hv_tf$`Reference Number of Connected Customers`
customer_no_adjust_lv_hv_asset <- gb_ref$customer_no_adjust_lv_hv_asset
for (n in 1:nrow(customer_no_adjust_lv_hv_asset)){
if (kva_per_customer == 'Default'){
adj_cust_no <- 1
break
} else if (kva_per_customer >= as.numeric(
customer_no_adjust_lv_hv_asset$Lower[n]) &
kva_per_customer < as.numeric(
customer_no_adjust_lv_hv_asset$Upper[n])){
adj_cust_no <-
customer_no_adjust_lv_hv_asset$
`No. of Customers to be used in the derivation of Customer Factor`[n]
break
}
}
adj_cust_no <-
adj_cust_no %>% stringr::str_match_all("[0-9]+") %>% unlist %>% as.numeric
customer_factor <- (adj_cust_no * no_customers) / ref_no_cust
# Customer sensitivity factor ---------------------------------------------
customer_sensitivity_factor <- 1 # See section 7.6.2.2, p. 89 in CNAIM (2021)
# Network perfomance consequence factor -----------------------------------
network_performance_consequence_factor <- customer_factor *
customer_sensitivity_factor
# Network performance cost of failure -------------------------------------
network_cof <- network_performance_consequence_factor * ncost
return((network_cof * GBP_to_DKK)/2)
}
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