R/zchunk_L2323.iron_steel.R
In JGCRI/gcamdata: Build the GCAM Input Datasets
Defines functions
module_energy_L2323.iron_steel
Documented in
module_energy_L2323.iron_steel
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_energy_L2323.iron_steel
#'
#' Compute a variety of final energy keyword, sector, share weight, and technology information for iron and steel-related GCAM inputs.
#'
#' @param command API command to execute
#' @param ... other optional parameters, depending on command
#' @return Depends on \code{command}: either a vector of required inputs,
#' a vector of output names, or (if \code{command} is "MAKE") all
#' the generated outputs: \code{L2323.SectorLogitTables[[ curr_table ]]$data}, \code{L2323.Supplysector_iron_steel}, \code{L2323.FinalEnergyKeyword_iron_steel},
#' \code{L2323.SubsectorLogitTables[[ curr_table ]]$data}, \code{L2323.SubsectorLogit_iron_steel}, \code{L2323.SubsectorShrwtFllt_iron_steel},
#' \code{L2323.SubsectorInterp_iron_steel}, \code{L2323.StubTech_iron_steel}, \code{L2323.GlobalTechShrwt_iron_steel}, \code{L2323.GlobalTechCoef_iron_steel},
#' \code{L2323.GlobalTechCost_iron_steel}, \code{L2323.GlobalTechCapture_iron_steel}, \code{L2323.StubTechProd_iron_steel}, \code{L2323.StubTechCalInput_iron_steel},
#' \code{L2323.StubTechCoef_iron_steel}, \code{L2323.PerCapitaBased_iron_steel}, \code{L2323.BaseService_iron_steel}, \code{L2323.PriceElasticity_iron_steel},
#' \code{object}. The corresponding file in the
#' original data system was \code{L2323.iron_steel.R} (energy level2).
#' @details The chunk provides final energy keyword, supplysector/subsector information, supplysector/subsector interpolation information, global technology share weight, global technology efficiency, global technology coefficients, global technology cost, price elasticity, stub technology information, stub technology interpolation information, stub technology calibrated inputs, and etc for iron and steel sector.
#' @importFrom assertthat assert_that
#' @importFrom dplyr arrange bind_rows distinct filter if_else group_by lag left_join mutate pull select
#' @importFrom tidyr gather spread
#' @author Yang Liu Sep 2019
module_energy_L2323.iron_steel <- function(command, ...) {
INCOME_ELASTICITY_OUTPUTS <- c("GCAM3",
paste0("gSSP", 1:5),
paste0("SSP", 1:5))
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/GCAM_region_names",
FILE = "energy/calibrated_techs",
FILE = "energy/A323.sector",
FILE = "energy/A323.subsector_interp",
FILE = "energy/A323.subsector_logit",
FILE = "energy/A323.subsector_shrwt",
FILE = "energy/A323.globaltech_coef",
FILE = "energy/A323.globaltech_cost",
FILE = "energy/A323.globaltech_shrwt",
FILE = "energy/A323.globaltech_co2capture",
FILE = "energy/A323.globaltech_retirement",
FILE = "energy/A323.demand",
"L1323.out_Mt_R_iron_steel_Yh",
"L1323.IO_GJkg_R_iron_steel_F_Yh"
#"L1323.in_EJ_R_iron_steel_F_Y"
))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L2323.Supplysector_iron_steel",
"L2323.FinalEnergyKeyword_iron_steel",
"L2323.SubsectorLogit_iron_steel",
"L2323.SubsectorShrwtFllt_iron_steel",
"L2323.SubsectorInterp_iron_steel",
"L2323.StubTech_iron_steel",
"L2323.GlobalTechShrwt_iron_steel",
"L2323.GlobalTechCoef_iron_steel",
"L2323.GlobalTechCost_iron_steel",
"L2323.GlobalTechCapture_iron_steel",
"L2323.GlobalTechShutdown_en",
"L2323.GlobalTechSCurve_en",
"L2323.GlobalTechLifetime_en",
"L2323.GlobalTechProfitShutdown_en",
"L2323.StubTechProd_iron_steel",
#"L2323.StubTechCalInput_iron_steel",
"L2323.StubTechCoef_iron_steel",
"L2323.PerCapitaBased_iron_steel",
"L2323.BaseService_iron_steel",
"L2323.PriceElasticity_iron_steel"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
calibrated_techs <- get_data(all_data, "energy/calibrated_techs")
A323.sector <- get_data(all_data, "energy/A323.sector", strip_attributes = TRUE)
A323.subsector_interp <- get_data(all_data, "energy/A323.subsector_interp", strip_attributes = TRUE)
A323.subsector_logit <- get_data(all_data, "energy/A323.subsector_logit", strip_attributes = TRUE)
A323.subsector_shrwt <- get_data(all_data, "energy/A323.subsector_shrwt", strip_attributes = TRUE)
A323.globaltech_coef <- get_data(all_data, "energy/A323.globaltech_coef", strip_attributes = TRUE)
A323.globaltech_cost <- get_data(all_data, "energy/A323.globaltech_cost", strip_attributes = TRUE)
A323.globaltech_shrwt <- get_data(all_data, "energy/A323.globaltech_shrwt", strip_attributes = TRUE)
A323.globaltech_co2capture <- get_data(all_data, "energy/A323.globaltech_co2capture", strip_attributes = TRUE)
A323.globaltech_retirement <- get_data(all_data, "energy/A323.globaltech_retirement", strip_attributes = TRUE)
A323.demand <- get_data(all_data, "energy/A323.demand", strip_attributes = TRUE)
L1323.out_Mt_R_iron_steel_Yh <- get_data(all_data, "L1323.out_Mt_R_iron_steel_Yh", strip_attributes = TRUE)
L1323.IO_GJkg_R_iron_steel_F_Yh <- get_data(all_data, "L1323.IO_GJkg_R_iron_steel_F_Yh")
# ===================================================
# 0. Give binding for variable names used in pipeline
year <- value <- GCAM_region_ID <- sector <- fuel <- year.fillout <- to.value <-
technology <- supplysector <- subsector <- minicam.energy.input <- coefficient <-
remove.fraction <- minicam.non.energy.input <- input.cost <- calibration <- calOutputValue <- subs.share.weight <- region <-
calibrated.value <- . <- scenario <- temp_lag <- base.service <- energy.final.demand <-
value.x <- value.y <- parameter <- year.x <- year.y <- tech.share.weight <- stub.technology <-
market.name <- sector.name <- subsector.name <- terminal_coef <- share.weight.year <- coeff <- NULL
# ===================================================
# 1. Perform computations
# Create tables to delete technologies and subsectors in regions where heat is not modeled as a fuel
# 1a. Supplysector information
# L2323.Supplysector_iron_steel: Supply sector information for iron and steel sector
A323.sector %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["Supplysector"]], LOGIT_TYPE_COLNAME), GCAM_region_names) ->
L2323.Supplysector_iron_steel
# L2323.FinalEnergyKeyword_iron_steel: Supply sector keywords for iron and steel sector
A323.sector %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["FinalEnergyKeyword"]], GCAM_region_names) %>%
na.omit ->
L2323.FinalEnergyKeyword_iron_steel
# 1b. Subsector information
# L2323.SubsectorLogit_iron_steel: Subsector logit exponents of iron and steel sector
A323.subsector_logit %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["SubsectorLogit"]], LOGIT_TYPE_COLNAME), GCAM_region_names) ->
L2323.SubsectorLogit_iron_steel
# and L2323.SubsectorShrwtFllt_iron_steel: Subsector shareweights of iron and steel sector
A323.subsector_shrwt %>%
filter(!is.na(year.fillout)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorShrwtFllt"]], GCAM_region_names) ->
L2323.SubsectorShrwtFllt_iron_steel
# L2323.SubsectorInterp_iron_steel: Subsector shareweight interpolation of iron and steel sector
A323.subsector_interp %>%
filter(is.na(to.value)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorInterp"]], GCAM_region_names) ->
L2323.SubsectorInterp_iron_steel
# 1c. Technology information
# L2323.StubTech_iron_steel: Identification of stub technologies of iron_steel
# Note: assuming that technology list in the shareweight table includes the full set (any others would default to a 0 shareweight)
A323.globaltech_shrwt %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["Tech"]], GCAM_region_names) %>%
rename(stub.technology = technology) ->
L2323.StubTech_iron_steel
# L2323.GlobalTechShrwt_iron_steel: Shareweights of global iron_steel technologies
A323.globaltech_shrwt %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology), year = c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, year) %>%
group_by(supplysector, subsector, technology) %>%
mutate(share.weight = approx_fun(year, value, rule = 1)) %>%
ungroup %>%
filter(year %in% c(MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "share.weight") ->
L2323.GlobalTechShrwt_iron_steel
# L2323.GlobalTechCoef_iron_steel: Energy inputs and coefficients of iron_steel technologies
A323.globaltech_coef %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology, minicam.energy.input), year = c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, minicam.energy.input, year) %>%
group_by(supplysector, subsector, technology, minicam.energy.input) %>%
mutate(coefficient = approx_fun(year, value, rule = 1),
coefficient = round(coefficient, energy.DIGITS_COEFFICIENT)) %>%
ungroup %>%
filter(year %in% c(MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechCoef"]]) ->
L2323.GlobalTechCoef_iron_steel
# Carbon capture rates from technologies with CCS
# L2323.GlobalTechCapture_iron_steel: CO2 capture fractions from global iron_steel production technologies with CCS
# No need to consider historical periods or intermittent technologies here
A323.globaltech_co2capture %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology), year = c(year, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, year) %>%
group_by(supplysector, subsector, technology) %>%
mutate(remove.fraction = approx_fun(year, value, rule = 1),
remove.fraction = round(remove.fraction, energy.DIGITS_REMOVE.FRACTION)) %>%
ungroup %>%
filter(year %in% MODEL_FUTURE_YEARS) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "remove.fraction") %>%
mutate(storage.market = energy.CO2.STORAGE.MARKET) ->
L2323.GlobalTechCapture_iron_steel
# Retirement information
A323.globaltech_retirement %>%
set_years() %>%
mutate(year = as.integer(year)) %>%
rename(sector.name = supplysector, subsector.name = subsector) ->
L2323.globaltech_retirement_base
# Copies first future year retirment information into all future years and appends back onto base year
L2323.globaltech_retirement_base %>%
mutate(year = as.integer(year)) %>%
filter(year == min(MODEL_FUTURE_YEARS)) %>%
repeat_add_columns(tibble(year = MODEL_FUTURE_YEARS)) %>%
select(-year.x) %>%
rename(year = year.y) ->
L2323.globaltech_retirement_future
# filters base years from original and then appends future years
L2323.globaltech_retirement_base %>%
mutate(year = as.integer(year)) %>%
filter(year == max(MODEL_BASE_YEARS)) %>%
bind_rows(L2323.globaltech_retirement_future) ->
L2323.globaltech_retirement
# Retirement may consist of any of three types of retirement function (phased, s-curve, or none)
# This section checks L2323.globaltech_retirement for each of these functions and creates a separate level 2 file for each
# All of these options have different headers, and all are allowed
if(any(!is.na(L2323.globaltech_retirement$shutdown.rate))) {
L2323.globaltech_retirement %>%
filter(!is.na(L2323.globaltech_retirement$shutdown.rate)) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "lifetime", "shutdown.rate") ->
L2323.GlobalTechShutdown_en
}
if(any(!is.na(L2323.globaltech_retirement$half.life))) {
L2323.globaltech_retirement %>%
filter(!is.na(L2323.globaltech_retirement$half.life)) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "lifetime", "steepness", "half.life") ->
L2323.GlobalTechSCurve_en
}
# L2323.GlobalTechLifetime_en: Global tech lifetime
if(any(is.na(L2323.globaltech_retirement$shutdown.rate) & is.na(L2323.globaltech_retirement$half.life))) {
L2323.globaltech_retirement %>%
filter(is.na(L2323.globaltech_retirement$shutdown.rate) & is.na(L2323.globaltech_retirement$half.life)) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "lifetime") ->
L2323.GlobalTechLifetime_en
}
# L2323.GlobalTechProfitShutdown_en: Global tech profit shutdown decider and parameters
if(any(!is.na(L2323.globaltech_retirement$median.shutdown.point))) {
L2323.globaltech_retirement %>%
filter(!is.na(L2323.globaltech_retirement$median.shutdown.point)) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "median.shutdown.point", "profit.shutdown.steepness") ->
L2323.GlobalTechProfitShutdown_en
}
# L2323.GlobalTechCost_iron_steel: Non-energy costs of global iron_steel manufacturing technologies
A323.globaltech_cost %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology, minicam.non.energy.input), year = c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, minicam.non.energy.input, year) %>%
group_by(supplysector, subsector, technology, minicam.non.energy.input) %>%
mutate(input.cost = approx_fun(year, value, rule = 1),
input.cost = round(input.cost, energy.DIGITS_COST)) %>%
ungroup %>%
filter(year %in% c(MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechCost"]]) ->
L2323.GlobalTechCost_iron_steel
# Calibration and region-specific data
# L2323.StubTechProd_iron_steel: calibrated iron_steel production
calibrated_techs %>%
filter(calibration == "output") %>% # Only take the tech IDs where the calibration is identified as output
select(sector, supplysector, subsector, technology) %>%
distinct ->
calibrated_techs_export # temporary tibble
L1323.out_Mt_R_iron_steel_Yh %>%
filter(year %in% MODEL_BASE_YEARS) %>%
mutate(calOutputValue = round(value, energy.DIGITS_CALOUTPUT), sector = "iron and steel") %>%
left_join(calibrated_techs_export %>% select(sector,supplysector, subsector,technology), by = c("sector","subsector")) %>%
left_join(GCAM_region_names, by = "GCAM_region_ID") %>%
mutate(stub.technology = technology,
share.weight.year = year,
subs.share.weight = 1,
tech.share.weight = if_else(subsector == technology , 1, 0),
calOutputValue = calOutputValue * tech.share.weight) %>%
unique() %>%
select(LEVEL2_DATA_NAMES[["StubTechProd"]]) ->
L2323.StubTechProd_iron_steel
# L2323.StubTechCoef_iron_steel: region-specific coefficients of iron_steel production technologies
# Take this as a given in all years for which data is available
calibrated_techs %>%
select(sector, fuel, supplysector, subsector, technology, minicam.energy.input) %>%
distinct ->
calibrated_techs_export # temporary tibble
L1323.IO_GJkg_R_iron_steel_F_Yh %>%
left_join(GCAM_region_names, by = "GCAM_region_ID") %>%
left_join(calibrated_techs, by = c("supplysector", "subsector", "technology", "fuel")) %>%
mutate(coefficient = round(coefficient, energy.DIGITS_COEFFICIENT),
stub.technology = technology,
market.name = region) %>%
select(LEVEL2_DATA_NAMES[["StubTechCoef"]]) ->
L2323.StubTechCoef_iron_steel_tmp
# Instead, interpolate the coefficients to these global default values in a specified period
L2323.StubTechCoef_iron_steel_tmp %>%
complete(nesting(region, supplysector, subsector, stub.technology, minicam.energy.input, market.name),
year = unique(c(MODEL_YEARS, energy.INDCOEF_CONVERGENCE_YR))) %>%
left_join(select(L2323.GlobalTechCoef_iron_steel %>% rename(terminal_coef = coefficient,supplysector = sector.name,subsector = subsector.name),
supplysector, subsector, technology, minicam.energy.input, terminal_coef, year),
by = c("supplysector", "subsector", stub.technology = "technology", "minicam.energy.input","year")) %>%
left_join(L2323.StubTechCoef_iron_steel_tmp %>%mutate(coeff = coefficient,coefficient=NULL),
by = c("region", "supplysector", "subsector", "stub.technology", "minicam.energy.input", "market.name", "year")) %>%
left_join(L2323.StubTechProd_iron_steel %>% select(-share.weight.year,-subs.share.weight,-tech.share.weight),
by = c("region", "supplysector", "subsector", "stub.technology", "year")) %>%
mutate(coefficient = if_else(year > MODEL_FINAL_BASE_YEAR , coeff, coefficient),
coefficient = if_else(year > MODEL_FINAL_BASE_YEAR & stub.technology == energy.IRON_STEEL.DEFAULT_COEF[1] , terminal_coef, coefficient),
coefficient = if_else(year > MODEL_FINAL_BASE_YEAR & minicam.energy.input == energy.IRON_STEEL.DEFAULT_COEF[2] , terminal_coef, coefficient),
coefficient = if_else(year > MODEL_FINAL_BASE_YEAR & minicam.energy.input == energy.IRON_STEEL.DEFAULT_COEF[3] , terminal_coef, coefficient)) %>%
select(-terminal_coef,-coeff,-calOutputValue) %>%
group_by(region, supplysector, subsector, stub.technology, minicam.energy.input) %>%
mutate(coefficient = round(approx_fun(year, coefficient,rule = 2), energy.DIGITS_COEFFICIENT)) %>%
ungroup() %>%
filter(year %in% MODEL_YEARS) -> # drop the terminal coef year if it's outside of the model years
L2323.StubTechCoef_iron_steel
# L2323.PerCapitaBased_iron_steel: per-capita based flag for iron_steel exports final demand
A323.demand %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["PerCapitaBased"]], GCAM_region_names) ->
L2323.PerCapitaBased_iron_steel
# L2323.BaseService_iron_steel: base-year service output of iron and steel
L2323.StubTechProd_iron_steel %>%
select(region, year, base.service = calOutputValue) %>%
mutate(energy.final.demand = A323.demand[["energy.final.demand"]]) %>%
group_by(region,year,energy.final.demand) %>%
summarise(base.service = sum(base.service)) %>%
ungroup() ->
L2323.BaseService_iron_steel
# L2323.PriceElasticity_iron_steel: price elasticity
A323.demand %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["PriceElasticity"]][LEVEL2_DATA_NAMES[["PriceElasticity"]] != "year"], GCAM_region_names) %>%
repeat_add_columns(tibble(year = MODEL_FUTURE_YEARS)) %>%
select(LEVEL2_DATA_NAMES[["PriceElasticity"]]) ->
L2323.PriceElasticity_iron_steel
# ===================================================
# Produce outputs
L2323.Supplysector_iron_steel %>%
add_title("Supply sector information for iron and steel sector") %>%
add_units("NA") %>%
add_comments("For iron and steel sector, the supply sector information (output.unit, input.unit, price.unit, logit.year.fillout, logit.exponent) from A323.sector is expended into all GCAM regions") %>%
add_legacy_name("L2323.Supplysector_iron_steel") %>%
add_precursors("energy/A323.sector", "common/GCAM_region_names") ->
L2323.Supplysector_iron_steel
L2323.FinalEnergyKeyword_iron_steel %>%
add_title("Supply sector keywords for iron and steel sector") %>%
add_units("NA") %>%
add_comments("For iron and steel sector, the supply sector final energy keywords from A323.sector are expended into all GCAM regions") %>%
add_legacy_name("L2323.FinalEnergyKeyword_iron_steel") %>%
add_precursors("energy/A323.sector", "common/GCAM_region_names") ->
L2323.FinalEnergyKeyword_iron_steel
L2323.SubsectorLogit_iron_steel %>%
add_title("Subsector logit exponents of iron and steel sector") %>%
add_units("Unitless") %>%
add_comments("For iron and steel sector, the subsector logit exponents from A323.subsector_logit are expanded into all GCAM regions") %>%
add_legacy_name("L2323.SubsectorLogit_iron_steel") %>%
add_precursors("energy/A323.subsector_logit", "common/GCAM_region_names") ->
L2323.SubsectorLogit_iron_steel
L2323.SubsectorShrwtFllt_iron_steel %>%
add_title("Subsector shareweights of iron and steel sector") %>%
add_units("unitless") %>%
add_comments("For iron and steel sector, the subsector shareweights from A323.subsector_shrwt are expanded into all GCAM regions") %>%
add_legacy_name("L2323.SubsectorShrwtFllt_iron_steel") %>%
add_precursors("energy/A323.subsector_shrwt", "common/GCAM_region_names") ->
L2323.SubsectorShrwtFllt_iron_steel
L2323.SubsectorInterp_iron_steel %>%
add_title("Subsector shareweight interpolation of iron and steel sector") %>%
add_units("NA") %>%
add_comments("For iron and steel sector, the subsector shareweight interpolation function infromation from A323.subsector_interp is expanded into all GCAM regions") %>%
add_legacy_name("L2323.SubsectorInterp_iron_steel") %>%
add_precursors("energy/A323.subsector_interp", "common/GCAM_region_names") ->
L2323.SubsectorInterp_iron_steel
L2323.StubTech_iron_steel %>%
add_title("Identification of stub technologies of iron and steel") %>%
add_units("NA") %>%
add_comments("For iron and steel sector, the stub technologies from A323.globaltech_shrwt are expanded into all GCAM regions") %>%
add_legacy_name("L2323.StubTech_iron_steel") %>%
add_precursors("energy/A323.globaltech_shrwt", "common/GCAM_region_names") ->
L2323.StubTech_iron_steel
L2323.GlobalTechShrwt_iron_steel %>%
add_title("Shareweights of global iron and steel technologies") %>%
add_units("Unitless") %>%
add_comments("For iron and steel sector, the share weights from A323.globaltech_shrwt are interpolated into all base years and future years") %>%
add_legacy_name("L2323.GlobalTechShrwt_iron_steel") %>%
add_precursors("energy/A323.globaltech_shrwt") ->
L2323.GlobalTechShrwt_iron_steel
L2323.GlobalTechCoef_iron_steel %>%
add_title("Energy inputs and coefficients of iron and steel technologies") %>%
add_units("scrap input is unitless (Mt scrap per Mt steel); all others are GJ per kg (EJ of energy per Mt of steel)") %>%
add_comments("For iron and steel sector, the energy use coefficients from A323.globaltech_coef are interpolated into all model years") %>%
add_legacy_name("L2323.GlobalTechCoef_iron_steel") %>%
add_precursors("energy/A323.globaltech_coef") ->
L2323.GlobalTechCoef_iron_steel
L2323.GlobalTechCost_iron_steel %>%
add_title("Non-energy costs of global iron and steel manufacturing technologies") %>%
add_units("1975$/kg for supplysector iron_steel; 1975$/GJ for supplysector process heat iron_steel") %>%
add_comments("For iron and steel sector, the Non-energy costs of global iron and steel manufacturing technologies are calculated then adjusted with CCS to include CO2 capture costs") %>%
add_legacy_name("L2323.GlobalTechCost_iron_steel") %>%
add_precursors("energy/A323.globaltech_cost", "energy/A323.globaltech_co2capture", "energy/A323.globaltech_coef") ->
L2323.GlobalTechCost_iron_steel
L2323.GlobalTechCapture_iron_steel %>%
add_title("CO2 capture fractions from global iron snf steel production technologies with CCS") %>%
add_units("Unitless") %>%
add_comments("For iron and steel sector, the remove fractions from A323.globaltech_co2capture are interpolated into all model years") %>%
add_legacy_name("L2323.GlobalTechCapture_iron_steel") %>%
add_precursors("energy/A323.globaltech_co2capture") ->
L2323.GlobalTechCapture_iron_steel
if(exists("L2323.GlobalTechShutdown_en")) {
L2323.GlobalTechShutdown_en %>%
add_title("Global tech lifetime for techs with shutdown rate") %>%
add_units("Lifetime in years") %>%
add_comments("Filters for any technology that uses a phased retirement function") %>%
add_legacy_name("L2323.GlobalTechShutdown_en") %>%
add_precursors("energy/A323.globaltech_retirement") ->
L2323.GlobalTechShutdown_en
} else {
missing_data() %>%
add_legacy_name("energy/L2323.GlobalTechShutdown_en") ->
L2323.GlobalTechShutdown_en
}
if(exists("L2323.GlobalTechSCurve_en")) {
L2323.GlobalTechSCurve_en %>%
add_title("Global tech lifetime for techs with s-curve retirement function") %>%
add_units("Lifetime in years, half-life in years") %>%
add_comments("Filters for any technology that uses an S-curve retirement function") %>%
add_legacy_name("L2323.GlobalTechSCurve_en") %>%
add_precursors("energy/A323.globaltech_retirement") ->
L2323.GlobalTechSCurve_en
} else {
missing_data() %>%
add_legacy_name("energy/L2323.GlobalTechSCurve_en") ->
L2323.GlobalTechSCurve_en
}
if(exists("L2323.GlobalTechLifetime_en")) {
L2323.GlobalTechLifetime_en %>%
add_title("Global tech lifetime for any technology with no retirement function") %>%
add_units("Lifetime in years") %>%
add_comments("Filters for any technology that has no phased or S-curve retirement function, empty by default.") %>%
add_legacy_name("L2323.GlobalTechLifetime_en") %>%
add_precursors("energy/A323.globaltech_retirement") ->
L2323.GlobalTechLifetime_en
} else {
missing_data() %>%
add_legacy_name("energy/L2323.GlobalTechLifetime_en") ->
L2323.GlobalTechLifetime_en
}
if(exists("L2323.GlobalTechProfitShutdown_en")) {
L2323.GlobalTechProfitShutdown_en %>%
add_title("Global tech profit shutdown decider and parameters") %>%
add_units("Unitless, used to determine shape of the function defining the relationship between shutdown rate and profitability") %>%
add_comments("Filters for any technologies that use a profit-based shutdown parameter") %>%
add_legacy_name("L2323.GlobalTechProfitShutdown_en") %>%
add_precursors("energy/A323.globaltech_retirement") ->
L2323.GlobalTechProfitShutdown_en
} else {
missing_data() %>%
add_legacy_name("energy/L2323.GlobalTechProfitShutdown_en") ->
L2323.GlobalTechProfitShutdown_en
}
L2323.StubTechProd_iron_steel %>%
add_title("calibrated iron and steel production") %>%
add_units("Mt") %>%
add_comments("Values are calculated using L1323.out_Mt_R_iron_steel_Yh then added GCAM region information and supplysector, subsector, and technology information") %>%
add_legacy_name("L2323.StubTechProd_iron_steel") %>%
add_precursors("energy/calibrated_techs", "L1323.out_Mt_R_iron_steel_Yh", "common/GCAM_region_names") ->
L2323.StubTechProd_iron_steel
L2323.StubTechCoef_iron_steel %>%
add_title("region-specific coefficients of iron and steel production technologies") %>%
add_units("scrap input is unitless (Mt scrap per Mt steel); all others are GJ per kg (EJ of energy per Mt of steel)") %>%
add_comments("Coefficients are calculated using L1323.IO_GJkg_R_iron_steel_F_Yh") %>%
add_legacy_name("L2323.StubTechCoef_iron_steel") %>%
add_precursors("energy/calibrated_techs", "L1323.IO_GJkg_R_iron_steel_F_Yh", "common/GCAM_region_names") ->
L2323.StubTechCoef_iron_steel
L2323.PerCapitaBased_iron_steel %>%
add_title("per-capita based flag for iron and steel exports final demand") %>%
add_units("NA") %>%
add_comments("Per-capita based flags for iron and steel from A323.demand are expanded into all GCAM regions") %>%
add_legacy_name("L2323.PerCapitaBased_iron_steel") %>%
add_precursors("energy/A323.demand", "common/GCAM_region_names") ->
L2323.PerCapitaBased_iron_steel
L2323.BaseService_iron_steel %>%
add_title("base-year service output of iron and steel") %>%
add_units("Mt") %>%
add_comments("Transformed from L2323.StubTechProd_iron_steel by adding energy.final.demand from A323.demand") %>%
add_legacy_name("L2323.BaseService_iron_steel") %>%
add_precursors("energy/A323.demand", "energy/calibrated_techs", "L1323.out_Mt_R_iron_steel_Yh", "common/GCAM_region_names") ->
L2323.BaseService_iron_steel
L2323.PriceElasticity_iron_steel %>%
add_title("price elasticity for iron and steel") %>%
add_units("Unitless") %>%
add_comments("The elasticity values from A323.demand are expanded into all GCAM_regions") %>%
add_legacy_name("L2323.PriceElasticity_iron_steel") %>%
add_precursors("energy/A323.demand", "common/GCAM_region_names") ->
L2323.PriceElasticity_iron_steel
return_data(L2323.Supplysector_iron_steel, L2323.FinalEnergyKeyword_iron_steel, L2323.SubsectorLogit_iron_steel,
L2323.SubsectorShrwtFllt_iron_steel, L2323.SubsectorInterp_iron_steel,
L2323.StubTech_iron_steel, L2323.GlobalTechShrwt_iron_steel,
L2323.GlobalTechCoef_iron_steel, L2323.GlobalTechCost_iron_steel, L2323.GlobalTechCapture_iron_steel, L2323.GlobalTechShutdown_en,
L2323.GlobalTechSCurve_en, L2323.GlobalTechLifetime_en, L2323.GlobalTechProfitShutdown_en,
L2323.StubTechProd_iron_steel, L2323.StubTechCoef_iron_steel,
L2323.PerCapitaBased_iron_steel, L2323.BaseService_iron_steel,
L2323.PriceElasticity_iron_steel)
} else {
stop("Unknown command")
}
}
JGCRI/gcamdata documentation built on March 21, 2023, 2:19 a.m.
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Defines functions module_energy_L2323.iron_steel
Documented in module_energy_L2323.iron_steel
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_energy_L2323.iron_steel
#'
#' Compute a variety of final energy keyword, sector, share weight, and technology information for iron and steel-related GCAM inputs.
#'
#' @param command API command to execute
#' @param ... other optional parameters, depending on command
#' @return Depends on \code{command}: either a vector of required inputs,
#' a vector of output names, or (if \code{command} is "MAKE") all
#' the generated outputs: \code{L2323.SectorLogitTables[[ curr_table ]]$data}, \code{L2323.Supplysector_iron_steel}, \code{L2323.FinalEnergyKeyword_iron_steel},
#' \code{L2323.SubsectorLogitTables[[ curr_table ]]$data}, \code{L2323.SubsectorLogit_iron_steel}, \code{L2323.SubsectorShrwtFllt_iron_steel},
#' \code{L2323.SubsectorInterp_iron_steel}, \code{L2323.StubTech_iron_steel}, \code{L2323.GlobalTechShrwt_iron_steel}, \code{L2323.GlobalTechCoef_iron_steel},
#' \code{L2323.GlobalTechCost_iron_steel}, \code{L2323.GlobalTechCapture_iron_steel}, \code{L2323.StubTechProd_iron_steel}, \code{L2323.StubTechCalInput_iron_steel},
#' \code{L2323.StubTechCoef_iron_steel}, \code{L2323.PerCapitaBased_iron_steel}, \code{L2323.BaseService_iron_steel}, \code{L2323.PriceElasticity_iron_steel},
#' \code{object}. The corresponding file in the
#' original data system was \code{L2323.iron_steel.R} (energy level2).
#' @details The chunk provides final energy keyword, supplysector/subsector information, supplysector/subsector interpolation information, global technology share weight, global technology efficiency, global technology coefficients, global technology cost, price elasticity, stub technology information, stub technology interpolation information, stub technology calibrated inputs, and etc for iron and steel sector.
#' @importFrom assertthat assert_that
#' @importFrom dplyr arrange bind_rows distinct filter if_else group_by lag left_join mutate pull select
#' @importFrom tidyr gather spread
#' @author Yang Liu Sep 2019
module_energy_L2323.iron_steel <- function(command, ...) {
INCOME_ELASTICITY_OUTPUTS <- c("GCAM3",
paste0("gSSP", 1:5),
paste0("SSP", 1:5))
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/GCAM_region_names",
FILE = "energy/calibrated_techs",
FILE = "energy/A323.sector",
FILE = "energy/A323.subsector_interp",
FILE = "energy/A323.subsector_logit",
FILE = "energy/A323.subsector_shrwt",
FILE = "energy/A323.globaltech_coef",
FILE = "energy/A323.globaltech_cost",
FILE = "energy/A323.globaltech_shrwt",
FILE = "energy/A323.globaltech_co2capture",
FILE = "energy/A323.globaltech_retirement",
FILE = "energy/A323.demand",
"L1323.out_Mt_R_iron_steel_Yh",
"L1323.IO_GJkg_R_iron_steel_F_Yh"
#"L1323.in_EJ_R_iron_steel_F_Y"
))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L2323.Supplysector_iron_steel",
"L2323.FinalEnergyKeyword_iron_steel",
"L2323.SubsectorLogit_iron_steel",
"L2323.SubsectorShrwtFllt_iron_steel",
"L2323.SubsectorInterp_iron_steel",
"L2323.StubTech_iron_steel",
"L2323.GlobalTechShrwt_iron_steel",
"L2323.GlobalTechCoef_iron_steel",
"L2323.GlobalTechCost_iron_steel",
"L2323.GlobalTechCapture_iron_steel",
"L2323.GlobalTechShutdown_en",
"L2323.GlobalTechSCurve_en",
"L2323.GlobalTechLifetime_en",
"L2323.GlobalTechProfitShutdown_en",
"L2323.StubTechProd_iron_steel",
#"L2323.StubTechCalInput_iron_steel",
"L2323.StubTechCoef_iron_steel",
"L2323.PerCapitaBased_iron_steel",
"L2323.BaseService_iron_steel",
"L2323.PriceElasticity_iron_steel"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
calibrated_techs <- get_data(all_data, "energy/calibrated_techs")
A323.sector <- get_data(all_data, "energy/A323.sector", strip_attributes = TRUE)
A323.subsector_interp <- get_data(all_data, "energy/A323.subsector_interp", strip_attributes = TRUE)
A323.subsector_logit <- get_data(all_data, "energy/A323.subsector_logit", strip_attributes = TRUE)
A323.subsector_shrwt <- get_data(all_data, "energy/A323.subsector_shrwt", strip_attributes = TRUE)
A323.globaltech_coef <- get_data(all_data, "energy/A323.globaltech_coef", strip_attributes = TRUE)
A323.globaltech_cost <- get_data(all_data, "energy/A323.globaltech_cost", strip_attributes = TRUE)
A323.globaltech_shrwt <- get_data(all_data, "energy/A323.globaltech_shrwt", strip_attributes = TRUE)
A323.globaltech_co2capture <- get_data(all_data, "energy/A323.globaltech_co2capture", strip_attributes = TRUE)
A323.globaltech_retirement <- get_data(all_data, "energy/A323.globaltech_retirement", strip_attributes = TRUE)
A323.demand <- get_data(all_data, "energy/A323.demand", strip_attributes = TRUE)
L1323.out_Mt_R_iron_steel_Yh <- get_data(all_data, "L1323.out_Mt_R_iron_steel_Yh", strip_attributes = TRUE)
L1323.IO_GJkg_R_iron_steel_F_Yh <- get_data(all_data, "L1323.IO_GJkg_R_iron_steel_F_Yh")
# ===================================================
# 0. Give binding for variable names used in pipeline
year <- value <- GCAM_region_ID <- sector <- fuel <- year.fillout <- to.value <-
technology <- supplysector <- subsector <- minicam.energy.input <- coefficient <-
remove.fraction <- minicam.non.energy.input <- input.cost <- calibration <- calOutputValue <- subs.share.weight <- region <-
calibrated.value <- . <- scenario <- temp_lag <- base.service <- energy.final.demand <-
value.x <- value.y <- parameter <- year.x <- year.y <- tech.share.weight <- stub.technology <-
market.name <- sector.name <- subsector.name <- terminal_coef <- share.weight.year <- coeff <- NULL
# ===================================================
# 1. Perform computations
# Create tables to delete technologies and subsectors in regions where heat is not modeled as a fuel
# 1a. Supplysector information
# L2323.Supplysector_iron_steel: Supply sector information for iron and steel sector
A323.sector %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["Supplysector"]], LOGIT_TYPE_COLNAME), GCAM_region_names) ->
L2323.Supplysector_iron_steel
# L2323.FinalEnergyKeyword_iron_steel: Supply sector keywords for iron and steel sector
A323.sector %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["FinalEnergyKeyword"]], GCAM_region_names) %>%
na.omit ->
L2323.FinalEnergyKeyword_iron_steel
# 1b. Subsector information
# L2323.SubsectorLogit_iron_steel: Subsector logit exponents of iron and steel sector
A323.subsector_logit %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["SubsectorLogit"]], LOGIT_TYPE_COLNAME), GCAM_region_names) ->
L2323.SubsectorLogit_iron_steel
# and L2323.SubsectorShrwtFllt_iron_steel: Subsector shareweights of iron and steel sector
A323.subsector_shrwt %>%
filter(!is.na(year.fillout)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorShrwtFllt"]], GCAM_region_names) ->
L2323.SubsectorShrwtFllt_iron_steel
# L2323.SubsectorInterp_iron_steel: Subsector shareweight interpolation of iron and steel sector
A323.subsector_interp %>%
filter(is.na(to.value)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorInterp"]], GCAM_region_names) ->
L2323.SubsectorInterp_iron_steel
# 1c. Technology information
# L2323.StubTech_iron_steel: Identification of stub technologies of iron_steel
# Note: assuming that technology list in the shareweight table includes the full set (any others would default to a 0 shareweight)
A323.globaltech_shrwt %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["Tech"]], GCAM_region_names) %>%
rename(stub.technology = technology) ->
L2323.StubTech_iron_steel
# L2323.GlobalTechShrwt_iron_steel: Shareweights of global iron_steel technologies
A323.globaltech_shrwt %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology), year = c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, year) %>%
group_by(supplysector, subsector, technology) %>%
mutate(share.weight = approx_fun(year, value, rule = 1)) %>%
ungroup %>%
filter(year %in% c(MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "share.weight") ->
L2323.GlobalTechShrwt_iron_steel
# L2323.GlobalTechCoef_iron_steel: Energy inputs and coefficients of iron_steel technologies
A323.globaltech_coef %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology, minicam.energy.input), year = c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, minicam.energy.input, year) %>%
group_by(supplysector, subsector, technology, minicam.energy.input) %>%
mutate(coefficient = approx_fun(year, value, rule = 1),
coefficient = round(coefficient, energy.DIGITS_COEFFICIENT)) %>%
ungroup %>%
filter(year %in% c(MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechCoef"]]) ->
L2323.GlobalTechCoef_iron_steel
# Carbon capture rates from technologies with CCS
# L2323.GlobalTechCapture_iron_steel: CO2 capture fractions from global iron_steel production technologies with CCS
# No need to consider historical periods or intermittent technologies here
A323.globaltech_co2capture %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology), year = c(year, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, year) %>%
group_by(supplysector, subsector, technology) %>%
mutate(remove.fraction = approx_fun(year, value, rule = 1),
remove.fraction = round(remove.fraction, energy.DIGITS_REMOVE.FRACTION)) %>%
ungroup %>%
filter(year %in% MODEL_FUTURE_YEARS) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "remove.fraction") %>%
mutate(storage.market = energy.CO2.STORAGE.MARKET) ->
L2323.GlobalTechCapture_iron_steel
# Retirement information
A323.globaltech_retirement %>%
set_years() %>%
mutate(year = as.integer(year)) %>%
rename(sector.name = supplysector, subsector.name = subsector) ->
L2323.globaltech_retirement_base
# Copies first future year retirment information into all future years and appends back onto base year
L2323.globaltech_retirement_base %>%
mutate(year = as.integer(year)) %>%
filter(year == min(MODEL_FUTURE_YEARS)) %>%
repeat_add_columns(tibble(year = MODEL_FUTURE_YEARS)) %>%
select(-year.x) %>%
rename(year = year.y) ->
L2323.globaltech_retirement_future
# filters base years from original and then appends future years
L2323.globaltech_retirement_base %>%
mutate(year = as.integer(year)) %>%
filter(year == max(MODEL_BASE_YEARS)) %>%
bind_rows(L2323.globaltech_retirement_future) ->
L2323.globaltech_retirement
# Retirement may consist of any of three types of retirement function (phased, s-curve, or none)
# This section checks L2323.globaltech_retirement for each of these functions and creates a separate level 2 file for each
# All of these options have different headers, and all are allowed
if(any(!is.na(L2323.globaltech_retirement$shutdown.rate))) {
L2323.globaltech_retirement %>%
filter(!is.na(L2323.globaltech_retirement$shutdown.rate)) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "lifetime", "shutdown.rate") ->
L2323.GlobalTechShutdown_en
}
if(any(!is.na(L2323.globaltech_retirement$half.life))) {
L2323.globaltech_retirement %>%
filter(!is.na(L2323.globaltech_retirement$half.life)) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "lifetime", "steepness", "half.life") ->
L2323.GlobalTechSCurve_en
}
# L2323.GlobalTechLifetime_en: Global tech lifetime
if(any(is.na(L2323.globaltech_retirement$shutdown.rate) & is.na(L2323.globaltech_retirement$half.life))) {
L2323.globaltech_retirement %>%
filter(is.na(L2323.globaltech_retirement$shutdown.rate) & is.na(L2323.globaltech_retirement$half.life)) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "lifetime") ->
L2323.GlobalTechLifetime_en
}
# L2323.GlobalTechProfitShutdown_en: Global tech profit shutdown decider and parameters
if(any(!is.na(L2323.globaltech_retirement$median.shutdown.point))) {
L2323.globaltech_retirement %>%
filter(!is.na(L2323.globaltech_retirement$median.shutdown.point)) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "median.shutdown.point", "profit.shutdown.steepness") ->
L2323.GlobalTechProfitShutdown_en
}
# L2323.GlobalTechCost_iron_steel: Non-energy costs of global iron_steel manufacturing technologies
A323.globaltech_cost %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology, minicam.non.energy.input), year = c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, minicam.non.energy.input, year) %>%
group_by(supplysector, subsector, technology, minicam.non.energy.input) %>%
mutate(input.cost = approx_fun(year, value, rule = 1),
input.cost = round(input.cost, energy.DIGITS_COST)) %>%
ungroup %>%
filter(year %in% c(MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechCost"]]) ->
L2323.GlobalTechCost_iron_steel
# Calibration and region-specific data
# L2323.StubTechProd_iron_steel: calibrated iron_steel production
calibrated_techs %>%
filter(calibration == "output") %>% # Only take the tech IDs where the calibration is identified as output
select(sector, supplysector, subsector, technology) %>%
distinct ->
calibrated_techs_export # temporary tibble
L1323.out_Mt_R_iron_steel_Yh %>%
filter(year %in% MODEL_BASE_YEARS) %>%
mutate(calOutputValue = round(value, energy.DIGITS_CALOUTPUT), sector = "iron and steel") %>%
left_join(calibrated_techs_export %>% select(sector,supplysector, subsector,technology), by = c("sector","subsector")) %>%
left_join(GCAM_region_names, by = "GCAM_region_ID") %>%
mutate(stub.technology = technology,
share.weight.year = year,
subs.share.weight = 1,
tech.share.weight = if_else(subsector == technology , 1, 0),
calOutputValue = calOutputValue * tech.share.weight) %>%
unique() %>%
select(LEVEL2_DATA_NAMES[["StubTechProd"]]) ->
L2323.StubTechProd_iron_steel
# L2323.StubTechCoef_iron_steel: region-specific coefficients of iron_steel production technologies
# Take this as a given in all years for which data is available
calibrated_techs %>%
select(sector, fuel, supplysector, subsector, technology, minicam.energy.input) %>%
distinct ->
calibrated_techs_export # temporary tibble
L1323.IO_GJkg_R_iron_steel_F_Yh %>%
left_join(GCAM_region_names, by = "GCAM_region_ID") %>%
left_join(calibrated_techs, by = c("supplysector", "subsector", "technology", "fuel")) %>%
mutate(coefficient = round(coefficient, energy.DIGITS_COEFFICIENT),
stub.technology = technology,
market.name = region) %>%
select(LEVEL2_DATA_NAMES[["StubTechCoef"]]) ->
L2323.StubTechCoef_iron_steel_tmp
# Instead, interpolate the coefficients to these global default values in a specified period
L2323.StubTechCoef_iron_steel_tmp %>%
complete(nesting(region, supplysector, subsector, stub.technology, minicam.energy.input, market.name),
year = unique(c(MODEL_YEARS, energy.INDCOEF_CONVERGENCE_YR))) %>%
left_join(select(L2323.GlobalTechCoef_iron_steel %>% rename(terminal_coef = coefficient,supplysector = sector.name,subsector = subsector.name),
supplysector, subsector, technology, minicam.energy.input, terminal_coef, year),
by = c("supplysector", "subsector", stub.technology = "technology", "minicam.energy.input","year")) %>%
left_join(L2323.StubTechCoef_iron_steel_tmp %>%mutate(coeff = coefficient,coefficient=NULL),
by = c("region", "supplysector", "subsector", "stub.technology", "minicam.energy.input", "market.name", "year")) %>%
left_join(L2323.StubTechProd_iron_steel %>% select(-share.weight.year,-subs.share.weight,-tech.share.weight),
by = c("region", "supplysector", "subsector", "stub.technology", "year")) %>%
mutate(coefficient = if_else(year > MODEL_FINAL_BASE_YEAR , coeff, coefficient),
coefficient = if_else(year > MODEL_FINAL_BASE_YEAR & stub.technology == energy.IRON_STEEL.DEFAULT_COEF[1] , terminal_coef, coefficient),
coefficient = if_else(year > MODEL_FINAL_BASE_YEAR & minicam.energy.input == energy.IRON_STEEL.DEFAULT_COEF[2] , terminal_coef, coefficient),
coefficient = if_else(year > MODEL_FINAL_BASE_YEAR & minicam.energy.input == energy.IRON_STEEL.DEFAULT_COEF[3] , terminal_coef, coefficient)) %>%
select(-terminal_coef,-coeff,-calOutputValue) %>%
group_by(region, supplysector, subsector, stub.technology, minicam.energy.input) %>%
mutate(coefficient = round(approx_fun(year, coefficient,rule = 2), energy.DIGITS_COEFFICIENT)) %>%
ungroup() %>%
filter(year %in% MODEL_YEARS) -> # drop the terminal coef year if it's outside of the model years
L2323.StubTechCoef_iron_steel
# L2323.PerCapitaBased_iron_steel: per-capita based flag for iron_steel exports final demand
A323.demand %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["PerCapitaBased"]], GCAM_region_names) ->
L2323.PerCapitaBased_iron_steel
# L2323.BaseService_iron_steel: base-year service output of iron and steel
L2323.StubTechProd_iron_steel %>%
select(region, year, base.service = calOutputValue) %>%
mutate(energy.final.demand = A323.demand[["energy.final.demand"]]) %>%
group_by(region,year,energy.final.demand) %>%
summarise(base.service = sum(base.service)) %>%
ungroup() ->
L2323.BaseService_iron_steel
# L2323.PriceElasticity_iron_steel: price elasticity
A323.demand %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["PriceElasticity"]][LEVEL2_DATA_NAMES[["PriceElasticity"]] != "year"], GCAM_region_names) %>%
repeat_add_columns(tibble(year = MODEL_FUTURE_YEARS)) %>%
select(LEVEL2_DATA_NAMES[["PriceElasticity"]]) ->
L2323.PriceElasticity_iron_steel
# ===================================================
# Produce outputs
L2323.Supplysector_iron_steel %>%
add_title("Supply sector information for iron and steel sector") %>%
add_units("NA") %>%
add_comments("For iron and steel sector, the supply sector information (output.unit, input.unit, price.unit, logit.year.fillout, logit.exponent) from A323.sector is expended into all GCAM regions") %>%
add_legacy_name("L2323.Supplysector_iron_steel") %>%
add_precursors("energy/A323.sector", "common/GCAM_region_names") ->
L2323.Supplysector_iron_steel
L2323.FinalEnergyKeyword_iron_steel %>%
add_title("Supply sector keywords for iron and steel sector") %>%
add_units("NA") %>%
add_comments("For iron and steel sector, the supply sector final energy keywords from A323.sector are expended into all GCAM regions") %>%
add_legacy_name("L2323.FinalEnergyKeyword_iron_steel") %>%
add_precursors("energy/A323.sector", "common/GCAM_region_names") ->
L2323.FinalEnergyKeyword_iron_steel
L2323.SubsectorLogit_iron_steel %>%
add_title("Subsector logit exponents of iron and steel sector") %>%
add_units("Unitless") %>%
add_comments("For iron and steel sector, the subsector logit exponents from A323.subsector_logit are expanded into all GCAM regions") %>%
add_legacy_name("L2323.SubsectorLogit_iron_steel") %>%
add_precursors("energy/A323.subsector_logit", "common/GCAM_region_names") ->
L2323.SubsectorLogit_iron_steel
L2323.SubsectorShrwtFllt_iron_steel %>%
add_title("Subsector shareweights of iron and steel sector") %>%
add_units("unitless") %>%
add_comments("For iron and steel sector, the subsector shareweights from A323.subsector_shrwt are expanded into all GCAM regions") %>%
add_legacy_name("L2323.SubsectorShrwtFllt_iron_steel") %>%
add_precursors("energy/A323.subsector_shrwt", "common/GCAM_region_names") ->
L2323.SubsectorShrwtFllt_iron_steel
L2323.SubsectorInterp_iron_steel %>%
add_title("Subsector shareweight interpolation of iron and steel sector") %>%
add_units("NA") %>%
add_comments("For iron and steel sector, the subsector shareweight interpolation function infromation from A323.subsector_interp is expanded into all GCAM regions") %>%
add_legacy_name("L2323.SubsectorInterp_iron_steel") %>%
add_precursors("energy/A323.subsector_interp", "common/GCAM_region_names") ->
L2323.SubsectorInterp_iron_steel
L2323.StubTech_iron_steel %>%
add_title("Identification of stub technologies of iron and steel") %>%
add_units("NA") %>%
add_comments("For iron and steel sector, the stub technologies from A323.globaltech_shrwt are expanded into all GCAM regions") %>%
add_legacy_name("L2323.StubTech_iron_steel") %>%
add_precursors("energy/A323.globaltech_shrwt", "common/GCAM_region_names") ->
L2323.StubTech_iron_steel
L2323.GlobalTechShrwt_iron_steel %>%
add_title("Shareweights of global iron and steel technologies") %>%
add_units("Unitless") %>%
add_comments("For iron and steel sector, the share weights from A323.globaltech_shrwt are interpolated into all base years and future years") %>%
add_legacy_name("L2323.GlobalTechShrwt_iron_steel") %>%
add_precursors("energy/A323.globaltech_shrwt") ->
L2323.GlobalTechShrwt_iron_steel
L2323.GlobalTechCoef_iron_steel %>%
add_title("Energy inputs and coefficients of iron and steel technologies") %>%
add_units("scrap input is unitless (Mt scrap per Mt steel); all others are GJ per kg (EJ of energy per Mt of steel)") %>%
add_comments("For iron and steel sector, the energy use coefficients from A323.globaltech_coef are interpolated into all model years") %>%
add_legacy_name("L2323.GlobalTechCoef_iron_steel") %>%
add_precursors("energy/A323.globaltech_coef") ->
L2323.GlobalTechCoef_iron_steel
L2323.GlobalTechCost_iron_steel %>%
add_title("Non-energy costs of global iron and steel manufacturing technologies") %>%
add_units("1975$/kg for supplysector iron_steel; 1975$/GJ for supplysector process heat iron_steel") %>%
add_comments("For iron and steel sector, the Non-energy costs of global iron and steel manufacturing technologies are calculated then adjusted with CCS to include CO2 capture costs") %>%
add_legacy_name("L2323.GlobalTechCost_iron_steel") %>%
add_precursors("energy/A323.globaltech_cost", "energy/A323.globaltech_co2capture", "energy/A323.globaltech_coef") ->
L2323.GlobalTechCost_iron_steel
L2323.GlobalTechCapture_iron_steel %>%
add_title("CO2 capture fractions from global iron snf steel production technologies with CCS") %>%
add_units("Unitless") %>%
add_comments("For iron and steel sector, the remove fractions from A323.globaltech_co2capture are interpolated into all model years") %>%
add_legacy_name("L2323.GlobalTechCapture_iron_steel") %>%
add_precursors("energy/A323.globaltech_co2capture") ->
L2323.GlobalTechCapture_iron_steel
if(exists("L2323.GlobalTechShutdown_en")) {
L2323.GlobalTechShutdown_en %>%
add_title("Global tech lifetime for techs with shutdown rate") %>%
add_units("Lifetime in years") %>%
add_comments("Filters for any technology that uses a phased retirement function") %>%
add_legacy_name("L2323.GlobalTechShutdown_en") %>%
add_precursors("energy/A323.globaltech_retirement") ->
L2323.GlobalTechShutdown_en
} else {
missing_data() %>%
add_legacy_name("energy/L2323.GlobalTechShutdown_en") ->
L2323.GlobalTechShutdown_en
}
if(exists("L2323.GlobalTechSCurve_en")) {
L2323.GlobalTechSCurve_en %>%
add_title("Global tech lifetime for techs with s-curve retirement function") %>%
add_units("Lifetime in years, half-life in years") %>%
add_comments("Filters for any technology that uses an S-curve retirement function") %>%
add_legacy_name("L2323.GlobalTechSCurve_en") %>%
add_precursors("energy/A323.globaltech_retirement") ->
L2323.GlobalTechSCurve_en
} else {
missing_data() %>%
add_legacy_name("energy/L2323.GlobalTechSCurve_en") ->
L2323.GlobalTechSCurve_en
}
if(exists("L2323.GlobalTechLifetime_en")) {
L2323.GlobalTechLifetime_en %>%
add_title("Global tech lifetime for any technology with no retirement function") %>%
add_units("Lifetime in years") %>%
add_comments("Filters for any technology that has no phased or S-curve retirement function, empty by default.") %>%
add_legacy_name("L2323.GlobalTechLifetime_en") %>%
add_precursors("energy/A323.globaltech_retirement") ->
L2323.GlobalTechLifetime_en
} else {
missing_data() %>%
add_legacy_name("energy/L2323.GlobalTechLifetime_en") ->
L2323.GlobalTechLifetime_en
}
if(exists("L2323.GlobalTechProfitShutdown_en")) {
L2323.GlobalTechProfitShutdown_en %>%
add_title("Global tech profit shutdown decider and parameters") %>%
add_units("Unitless, used to determine shape of the function defining the relationship between shutdown rate and profitability") %>%
add_comments("Filters for any technologies that use a profit-based shutdown parameter") %>%
add_legacy_name("L2323.GlobalTechProfitShutdown_en") %>%
add_precursors("energy/A323.globaltech_retirement") ->
L2323.GlobalTechProfitShutdown_en
} else {
missing_data() %>%
add_legacy_name("energy/L2323.GlobalTechProfitShutdown_en") ->
L2323.GlobalTechProfitShutdown_en
}
L2323.StubTechProd_iron_steel %>%
add_title("calibrated iron and steel production") %>%
add_units("Mt") %>%
add_comments("Values are calculated using L1323.out_Mt_R_iron_steel_Yh then added GCAM region information and supplysector, subsector, and technology information") %>%
add_legacy_name("L2323.StubTechProd_iron_steel") %>%
add_precursors("energy/calibrated_techs", "L1323.out_Mt_R_iron_steel_Yh", "common/GCAM_region_names") ->
L2323.StubTechProd_iron_steel
L2323.StubTechCoef_iron_steel %>%
add_title("region-specific coefficients of iron and steel production technologies") %>%
add_units("scrap input is unitless (Mt scrap per Mt steel); all others are GJ per kg (EJ of energy per Mt of steel)") %>%
add_comments("Coefficients are calculated using L1323.IO_GJkg_R_iron_steel_F_Yh") %>%
add_legacy_name("L2323.StubTechCoef_iron_steel") %>%
add_precursors("energy/calibrated_techs", "L1323.IO_GJkg_R_iron_steel_F_Yh", "common/GCAM_region_names") ->
L2323.StubTechCoef_iron_steel
L2323.PerCapitaBased_iron_steel %>%
add_title("per-capita based flag for iron and steel exports final demand") %>%
add_units("NA") %>%
add_comments("Per-capita based flags for iron and steel from A323.demand are expanded into all GCAM regions") %>%
add_legacy_name("L2323.PerCapitaBased_iron_steel") %>%
add_precursors("energy/A323.demand", "common/GCAM_region_names") ->
L2323.PerCapitaBased_iron_steel
L2323.BaseService_iron_steel %>%
add_title("base-year service output of iron and steel") %>%
add_units("Mt") %>%
add_comments("Transformed from L2323.StubTechProd_iron_steel by adding energy.final.demand from A323.demand") %>%
add_legacy_name("L2323.BaseService_iron_steel") %>%
add_precursors("energy/A323.demand", "energy/calibrated_techs", "L1323.out_Mt_R_iron_steel_Yh", "common/GCAM_region_names") ->
L2323.BaseService_iron_steel
L2323.PriceElasticity_iron_steel %>%
add_title("price elasticity for iron and steel") %>%
add_units("Unitless") %>%
add_comments("The elasticity values from A323.demand are expanded into all GCAM_regions") %>%
add_legacy_name("L2323.PriceElasticity_iron_steel") %>%
add_precursors("energy/A323.demand", "common/GCAM_region_names") ->
L2323.PriceElasticity_iron_steel
return_data(L2323.Supplysector_iron_steel, L2323.FinalEnergyKeyword_iron_steel, L2323.SubsectorLogit_iron_steel,
L2323.SubsectorShrwtFllt_iron_steel, L2323.SubsectorInterp_iron_steel,
L2323.StubTech_iron_steel, L2323.GlobalTechShrwt_iron_steel,
L2323.GlobalTechCoef_iron_steel, L2323.GlobalTechCost_iron_steel, L2323.GlobalTechCapture_iron_steel, L2323.GlobalTechShutdown_en,
L2323.GlobalTechSCurve_en, L2323.GlobalTechLifetime_en, L2323.GlobalTechProfitShutdown_en,
L2323.StubTechProd_iron_steel, L2323.StubTechCoef_iron_steel,
L2323.PerCapitaBased_iron_steel, L2323.BaseService_iron_steel,
L2323.PriceElasticity_iron_steel)
} else {
stop("Unknown command")
}
}
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