R/zchunk_L261.Cstorage.R
In rohmin9122/gcam-korea-release: Build the GCAM-Korea Input Datasets
Defines functions
module_energy_L261.Cstorage
Documented in
module_energy_L261.Cstorage
#' module_energy_L261.Cstorage
#'
#' Calculate carbon storage resource supply curves, shareweights, technology coefficients and costs, and other carbon storage information.
#'
#' @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{L261.DepRsrc}, \code{L261.UnlimitRsrc}, \code{L261.DepRsrcCurves_C}, \code{L261.SectorLogitTables[[ curr_table ]]$data}, \code{L261.Supplysector_C}, \code{L261.SubsectorLogitTables[[ curr_table ]]$data}, \code{L261.SubsectorLogit_C}, \code{L261.SubsectorShrwtFllt_C}, \code{L261.StubTech_C}, \code{L261.GlobalTechCoef_C}, \code{L261.GlobalTechCost_C}, \code{L261.GlobalTechShrwt_C}, \code{L261.GlobalTechCost_C_High}, \code{L261.GlobalTechShrwt_C_nooffshore}, \code{L261.DepRsrcCurves_C_high}, \code{L261.DepRsrcCurves_C_low}, \code{L261.DepRsrcCurves_C_lowest}. The corresponding file in the
#' original data system was \code{L261.Cstorage.R} (energy level2).
#' @details The following fifteen tables pertaining to carbon storage properties are generated:
#' \itemize{
#' \item{Carbon storage information}
#' \item{Unlimited carbon storage information}
#' \item{Supply curve of carbon storage resources}
#' \item{High supply curve of onshore carbon storage resources}
#' \item{Low supply curve of onshore carbon storage resources}
#' \item{Lowest supply curve of onshore carbon storage resources}
#' \item{Carbon storage sector information}
#' \item{Subsector logit exponents of carbon storage sector}
#' \item{Subsector shareweights of carbon storage sectors}
#' \item{Identification of stub technologies of carbon storage}
#' \item{Carbon storage global technology coefficients across base model years}
#' \item{Carbon storage global technology costs across base model years}
#' \item{Carbon storage global technology costs across base model years, high price scenario}
#' \item{Shareweights of carbon storage technologies across base model years}
#' \item{Shareweights of offshore carbon storage technologies}
#' }
#' @importFrom assertthat assert_that
#' @importFrom dplyr filter mutate select
#' @importFrom tidyr gather spread
#' @author AJS August 2017
module_energy_L261.Cstorage <- function(command, ...) {
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/GCAM_region_names",
FILE = "energy/A61.rsrc_info",
FILE = "energy/A61.sector",
FILE = "energy/A61.subsector_logit",
FILE = "energy/A61.subsector_shrwt",
FILE = "energy/A61.globaltech_coef",
FILE = "energy/A61.globaltech_cost",
FILE = "energy/A61.globaltech_shrwt",
"L161.RsrcCurves_MtC_R"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L261.DepRsrc",
"L261.UnlimitRsrc",
"L261.DepRsrcCurves_C",
"L261.Supplysector_C",
"L261.SubsectorLogit_C",
"L261.SubsectorShrwtFllt_C",
"L261.StubTech_C",
"L261.GlobalTechCoef_C",
"L261.GlobalTechCost_C",
"L261.GlobalTechShrwt_C",
"L261.GlobalTechCost_C_High",
"L261.GlobalTechShrwt_C_nooffshore",
"L261.DepRsrcCurves_C_high",
"L261.DepRsrcCurves_C_low",
"L261.DepRsrcCurves_C_lowest"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
A61.rsrc_info <- get_data(all_data, "energy/A61.rsrc_info")
A61.sector <- get_data(all_data, "energy/A61.sector")
A61.subsector_logit <- get_data(all_data, "energy/A61.subsector_logit")
A61.subsector_shrwt <- get_data(all_data, "energy/A61.subsector_shrwt")
A61.globaltech_coef <- get_data(all_data, "energy/A61.globaltech_coef")
A61.globaltech_cost <- get_data(all_data, "energy/A61.globaltech_cost")
A61.globaltech_shrwt <- get_data(all_data, "energy/A61.globaltech_shrwt")
L161.RsrcCurves_MtC_R <- get_data(all_data, "L161.RsrcCurves_MtC_R")
# ===================================================
# Silence package notes
. <- available <- capacity.factor <- curr_table <- extractioncost <-
grade <- logit.type <- minicam.energy.input <- minicam.non.energy.input <-
`output-unit` <- `price-unit` <- resource <- resource_type <- share.weight <-
subresource <- subsector <- subsector.name <- supplysector <- technology <-
value <- year <- region <- depresource <- output.unit <- price.unit <-
market <- logit.exponent <- coefficient <- input.cost <- NULL
# A
# Create tables for carbon storage resource information
# A61.rsrc_info provides carbon storage resource info (output unit, price unit, capacity factor, market, etc)
A61.rsrc_info %>%
# Expand table to incorporate GCAM region names (use ID to ensure correct region ordering)
# We will use these specific region names to replace the broad term, regional, in the market column.
repeat_add_columns(GCAM_region_names) %>%
# Reset regional markets to the names of the specific regions
mutate(market = replace(market, market == "regional", region[market == "regional"]),
capacity.factor = as.numeric(capacity.factor)) %>%
rename(output.unit = `output-unit`, price.unit = `price-unit`) ->
L261.rsrc_info
# Split different types of resources into separate tables
# Create table reporting carbon storage information for unlimited resources only
L261.rsrc_info %>%
filter(resource_type == "unlimited-resource") %>%
select(region, unlimited.resource = resource, output.unit, price.unit, market, capacity.factor) ->
L261.UnlimitRsrc # This is a final ouput table.
# Create table reporting carbon storage information for depletable resources only
L261.rsrc_info %>%
filter(resource_type == "depresource") %>%
select(region, depresource = resource, output.unit, price.unit, market) ->
L261.DepRsrc # This is a final ouput table.
# B
# Supply curves of carbon storage resources
# First, define number of decimal places
DIGITS_COST <- 1
# L161.RsrcCurves_MtC_R reports carbon storage resource supply curves by GCAM region.
L161.RsrcCurves_MtC_R %>%
# Match in GCAM region names using region ID
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
mutate(available = round(available, DIGITS_COST)) %>%
select(region, depresource = resource, subresource, grade, available, extractioncost) ->
L261.DepRsrcCurves_C # This is a final output table.
# Calculate three different supply curves of carbon storage resources: high, low, and lowest.
# Multiply the extraction cost by its respective multiplier below.
# Note that the multipliers were created for the SSPs and that high, low, and lowest is the level of CCS use and not cost.
HI_CCS_COST_MULT <- 0.8
LO_CCS_COST_MULT <- 3
LOWEST_CCS_COST_MULT <- 10
# Note that these will produce final output tables.
# High supply curves of carbon storage resources
L261.DepRsrcCurves_C_high <- mutate(L261.DepRsrcCurves_C, extractioncost = extractioncost * HI_CCS_COST_MULT)
# Low supply curves of carbon storage resources
L261.DepRsrcCurves_C_low <- mutate(L261.DepRsrcCurves_C, extractioncost = extractioncost * LO_CCS_COST_MULT)
# Lowest supply curves of carbon storage resources
L261.DepRsrcCurves_C_lowest <- mutate(L261.DepRsrcCurves_C, extractioncost = extractioncost * LOWEST_CCS_COST_MULT)
# C
# Carbon storage sector information
A61.sector %>%
mutate(logit.exponent = as.numeric(logit.exponent)) %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["Supplysector"]], LOGIT_TYPE_COLNAME),
GCAM_region_names = GCAM_region_names) ->
L261.Supplysector_C # This is a final output table.
# D
# Subsector information
# Subsector logit exponents of carbon storage sector
A61.subsector_logit %>%
mutate(logit.exponent = as.numeric(logit.exponent)) %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["SubsectorLogit"]], LOGIT_TYPE_COLNAME),
GCAM_region_names = GCAM_region_names) ->
L261.SubsectorLogit_C # This is a final output table.
# Subsector shareweights of carbon storage sectors
A61.subsector_shrwt %>%
mutate(share.weight = as.numeric(share.weight)) %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["SubsectorShrwtFllt"]], LOGIT_TYPE_COLNAME),
GCAM_region_names = GCAM_region_names) ->
L261.SubsectorShrwtFllt_C # This is a final output table.
# E
# Technology information
# Identification of stub technologies of carbon storage
# A61.globaltech_shrwt reports carbon storage technology shareweights
# Note: assuming that the technology list in the shareweight table includes the full set (any others would default to a 0 shareweight)
A61.globaltech_shrwt %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["Tech"]],
GCAM_region_names = GCAM_region_names) %>%
select(region, supplysector, subsector, stub.technology = technology) ->
L261.StubTech_C # This is a final output table.
# Energy inputs and coefficients of global technologies for carbon storage
# A61.globaltech_coef reports carbon storage global technology coefficients
A61.globaltech_coef %>%
gather_years %>%
# Expand table to include all model base and future years
complete(year = c(year, MODEL_YEARS), nesting(supplysector, subsector, technology, minicam.energy.input)) %>%
# Extrapolate to fill out values for all years
# Rule 2 is used so years outside of min-max range are assigned values from closest data, as opposed to NAs
mutate(coefficient = approx_fun(year, value, rule = 2)) %>%
filter(year %in% MODEL_YEARS) %>% # This will drop 1971
# Assign the columns "sector.name" and "subsector.name", consistent with the location info of a global technology
select(sector.name = supplysector, subsector.name = subsector, technology, year, minicam.energy.input, coefficient) ->
L261.GlobalTechCoef_C # This is a final output table.
# Costs of global technologies
# A61.globaltech_cost reports carbon storage offshore storage cost (1975$/tCO2)
A61.globaltech_cost %>%
gather_years %>%
# Expand table to include all model base and future years
complete(year = c(year, MODEL_YEARS), nesting(supplysector, subsector, technology, minicam.non.energy.input)) %>%
# Extrapolate to fill out values for all years
# Rule 2 is used so years outside of min-max range are assigned values from closest data, as opposed to NAs
mutate(input.cost = approx_fun(year, value, rule = 2)) %>%
filter(year %in% MODEL_YEARS) %>% # This will drop 1971
# Assign the columns "sector.name" and "subsector.name", consistent with the location info of a global technology
select(sector.name = supplysector, subsector.name = subsector, technology, year, minicam.non.energy.input, input.cost) ->
L261.GlobalTechCost_C # This is a final output table.
# High costs of global technologies for carbon storage -- this prices out CCS
L261.GlobalTechCost_C %>%
mutate(subsector.name = "onshore carbon-storage",
technology = "onshore carbon-storage") %>%
bind_rows(L261.GlobalTechCost_C) %>%
# Price out CCS by using storage cost that is very high (i.e., $10,000/tCO2)
mutate(input.cost = 10000) -> # 1975$/tCO2
L261.GlobalTechCost_C_High # This is a final output table.
# Shareweights of global technologies for energy transformation
A61.globaltech_shrwt %>%
gather_years %>%
# Expand table to include all model base and future years
complete(year = c(year, MODEL_YEARS), nesting(supplysector, subsector, technology)) %>%
# Extrapolate to fill out values for all years
# Rule 2 is used so years outside of min-max range are assigned values from closest data, as opposed to NAs
mutate(share.weight = approx_fun(year, value, rule = 2)) %>%
filter(year %in% MODEL_YEARS) %>% # This will drop 1971
# Assign the columns "sector.name" and "subsector.name", consistent with the location info of a global technology
select(sector.name = supplysector, subsector.name = subsector, technology, year, share.weight) ->
L261.GlobalTechShrwt_C # This is a final output table.
# Use zero shareweights for offshore storage
L261.GlobalTechShrwt_C %>%
filter(subsector.name == "offshore carbon-storage") %>%
mutate(share.weight = 0) ->
L261.GlobalTechShrwt_C_nooffshore # This is a final output table.
# ===================================================
L261.DepRsrc %>%
add_title("Carbon storage information") %>%
add_units("Output unit as listed (MtC), price unit as listed (1990$/tC)") %>%
add_comments("Carbon storage resource information was expanded to include GCAM region names") %>%
add_comments("and filtered for only depletable resources") %>%
add_legacy_name("L261.DepRsrc") %>%
add_precursors("common/GCAM_region_names", "energy/A61.rsrc_info") ->
L261.DepRsrc
L261.UnlimitRsrc %>%
add_title("Unlimited carbon storage information") %>%
add_units("Output unit as listed (MtC), price unit as listed (1990$/tC), capacity factor is unitless") %>%
add_comments("Carbon storage resource information was expanded to include GCAM region names") %>%
add_comments("and filtered for only unlimited resources (i.e., offshore)") %>%
add_legacy_name("L261.UnlimitRsrc") %>%
add_precursors("common/GCAM_region_names", "energy/A61.rsrc_info") ->
L261.UnlimitRsrc
L261.DepRsrcCurves_C %>%
add_title("Supply curve of carbon storage resources") %>%
add_units("Available in MtCO2, Extraction Cost in 1990$/tCO2") %>%
add_comments("GCAM region names were added to the resource supply curves generated in level 1") %>%
add_legacy_name("L261.DepRsrcCurves_C") %>%
add_precursors("common/GCAM_region_names", "L161.RsrcCurves_MtC_R") ->
L261.DepRsrcCurves_C
L261.DepRsrcCurves_C_high %>%
add_title("High supply curve of onshore carbon storage resources") %>%
add_units("Available in MtCO2, Extraction Cost in 1990$/tCO2") %>%
add_comments("A multiplier (based on high level of CCS use) was applied to the extraction cost to generate a high supply curve") %>%
add_legacy_name("L261.DepRsrcCurves_C_high") %>%
add_precursors("common/GCAM_region_names", "L161.RsrcCurves_MtC_R") ->
L261.DepRsrcCurves_C_high
L261.DepRsrcCurves_C_low %>%
add_title("Low supply curve of onshore carbon storage resources") %>%
add_units("Available in MtCO2, Extraction Cost in 1990$/tCO2") %>%
add_comments("A multiplier (based on low level of CCS use) was applied to the extraction cost to generate a low supply curve") %>%
add_legacy_name("L261.DepRsrcCurves_C_low") %>%
add_precursors("common/GCAM_region_names", "L161.RsrcCurves_MtC_R") ->
L261.DepRsrcCurves_C_low
L261.DepRsrcCurves_C_lowest %>%
add_title("Lowest supply curve of onshore carbon storage resources") %>%
add_units("Available in MtCO2, Extraction Cost in 1990$/tCO2") %>%
add_comments("A multiplier (based on lowest level of CCS use) was applied to the extraction cost to generate a lowest supply curve") %>%
add_legacy_name("L261.DepRsrcCurves_C_lowest") %>%
add_precursors("common/GCAM_region_names", "L161.RsrcCurves_MtC_R") ->
L261.DepRsrcCurves_C_lowest
L261.Supplysector_C %>%
add_title("Carbon storage sector information") %>%
add_units("Output, input, and price units are as listed; exponent is unitless") %>%
add_comments("Carbon storage sector information was expanded to include GCAM region names") %>%
add_legacy_name("L261.Supplysector_C") %>%
add_precursors("common/GCAM_region_names", "energy/A61.sector") ->
L261.Supplysector_C
L261.SubsectorLogit_C %>%
add_title("Subsector logit exponents of carbon storage sector") %>%
add_units("Unitless") %>%
add_comments("Table on subsector logit exponents was expanded to include GCAM region names") %>%
add_legacy_name("L261.SubsectorLogit_C") %>%
add_precursors("common/GCAM_region_names", "energy/A61.subsector_logit") ->
L261.SubsectorLogit_C
L261.SubsectorShrwtFllt_C %>%
add_title("Subsector shareweights of carbon storage sectors") %>%
add_units("Unitless") %>%
add_comments("Table on subsector shareweights was expanded to include GCAM region names") %>%
add_legacy_name("L261.SubsectorShrwtFllt_C") %>%
add_precursors("common/GCAM_region_names", "energy/A61.subsector_shrwt") ->
L261.SubsectorShrwtFllt_C
L261.StubTech_C %>%
add_title("Identification of stub technologies of carbon storage") %>%
add_units("Not Applicable") %>%
add_comments("Technology list in the global shareweight table for carbon storage was expanded to include GCAM regions") %>%
add_legacy_name("L261.StubTech_C") %>%
add_precursors("common/GCAM_region_names", "energy/A61.globaltech_shrwt") ->
L261.StubTech_C
L261.GlobalTechCoef_C %>%
add_title("Carbon storage global technology coefficients across base model years") %>%
add_units("Unitless") %>%
add_comments("Global technology coefficients were interpolated across all base model years") %>%
add_legacy_name("L261.GlobalTechCoef_C") %>%
add_precursors("energy/A61.globaltech_coef") ->
L261.GlobalTechCoef_C
L261.GlobalTechCost_C %>%
add_title("Carbon storage global technology costs across base model years") %>%
add_units("1975$/tCO2") %>%
add_comments("Global technology coefficients were interpolated across all base model years") %>%
add_legacy_name("L261.GlobalTechCost_C") %>%
add_precursors("energy/A61.globaltech_cost") ->
L261.GlobalTechCost_C
L261.GlobalTechCost_C_High %>%
add_title("Carbon storage global technology costs across base model years (high price scenario)") %>%
add_units("1975$/tCO2") %>%
add_comments("Assigned onshore and offshore carbon storage technologies a high price to price out CCS") %>%
add_legacy_name("L261.GlobalTechCost_C_High") %>%
add_precursors("energy/A61.globaltech_cost") ->
L261.GlobalTechCost_C_High
L261.GlobalTechShrwt_C %>%
add_title("Shareweights of carbon storage technologies across base model years") %>%
add_units("Unitless") %>%
add_comments("Shareweights of global technologies for energy transformation were interpolated across all base model years") %>%
add_legacy_name("L261.GlobalTechShrwt_C") %>%
add_precursors("energy/A61.globaltech_shrwt") ->
L261.GlobalTechShrwt_C
L261.GlobalTechShrwt_C_nooffshore %>%
add_title("Shareweights of offshore carbon storage technologies") %>%
add_units("Unitless") %>%
add_comments("Subset shareweight table for offshore only. Assigned them shareweights of zero") %>%
add_legacy_name("L261.GlobalTechShrwt_C_nooffshore") %>%
add_precursors("energy/A61.globaltech_shrwt") ->
L261.GlobalTechShrwt_C_nooffshore
return_data(L261.DepRsrc, L261.UnlimitRsrc, L261.DepRsrcCurves_C, L261.Supplysector_C, L261.SubsectorLogit_C, L261.SubsectorShrwtFllt_C, L261.StubTech_C, L261.GlobalTechCoef_C, L261.GlobalTechCost_C, L261.GlobalTechShrwt_C, L261.GlobalTechCost_C_High, L261.GlobalTechShrwt_C_nooffshore, L261.DepRsrcCurves_C_high, L261.DepRsrcCurves_C_low, L261.DepRsrcCurves_C_lowest)
} else {
stop("Unknown command")
}
}
rohmin9122/gcam-korea-release documentation built on Nov. 26, 2020, 8:11 a.m.
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Defines functions module_energy_L261.Cstorage
Documented in module_energy_L261.Cstorage
#' module_energy_L261.Cstorage
#'
#' Calculate carbon storage resource supply curves, shareweights, technology coefficients and costs, and other carbon storage information.
#'
#' @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{L261.DepRsrc}, \code{L261.UnlimitRsrc}, \code{L261.DepRsrcCurves_C}, \code{L261.SectorLogitTables[[ curr_table ]]$data}, \code{L261.Supplysector_C}, \code{L261.SubsectorLogitTables[[ curr_table ]]$data}, \code{L261.SubsectorLogit_C}, \code{L261.SubsectorShrwtFllt_C}, \code{L261.StubTech_C}, \code{L261.GlobalTechCoef_C}, \code{L261.GlobalTechCost_C}, \code{L261.GlobalTechShrwt_C}, \code{L261.GlobalTechCost_C_High}, \code{L261.GlobalTechShrwt_C_nooffshore}, \code{L261.DepRsrcCurves_C_high}, \code{L261.DepRsrcCurves_C_low}, \code{L261.DepRsrcCurves_C_lowest}. The corresponding file in the
#' original data system was \code{L261.Cstorage.R} (energy level2).
#' @details The following fifteen tables pertaining to carbon storage properties are generated:
#' \itemize{
#' \item{Carbon storage information}
#' \item{Unlimited carbon storage information}
#' \item{Supply curve of carbon storage resources}
#' \item{High supply curve of onshore carbon storage resources}
#' \item{Low supply curve of onshore carbon storage resources}
#' \item{Lowest supply curve of onshore carbon storage resources}
#' \item{Carbon storage sector information}
#' \item{Subsector logit exponents of carbon storage sector}
#' \item{Subsector shareweights of carbon storage sectors}
#' \item{Identification of stub technologies of carbon storage}
#' \item{Carbon storage global technology coefficients across base model years}
#' \item{Carbon storage global technology costs across base model years}
#' \item{Carbon storage global technology costs across base model years, high price scenario}
#' \item{Shareweights of carbon storage technologies across base model years}
#' \item{Shareweights of offshore carbon storage technologies}
#' }
#' @importFrom assertthat assert_that
#' @importFrom dplyr filter mutate select
#' @importFrom tidyr gather spread
#' @author AJS August 2017
module_energy_L261.Cstorage <- function(command, ...) {
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/GCAM_region_names",
FILE = "energy/A61.rsrc_info",
FILE = "energy/A61.sector",
FILE = "energy/A61.subsector_logit",
FILE = "energy/A61.subsector_shrwt",
FILE = "energy/A61.globaltech_coef",
FILE = "energy/A61.globaltech_cost",
FILE = "energy/A61.globaltech_shrwt",
"L161.RsrcCurves_MtC_R"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L261.DepRsrc",
"L261.UnlimitRsrc",
"L261.DepRsrcCurves_C",
"L261.Supplysector_C",
"L261.SubsectorLogit_C",
"L261.SubsectorShrwtFllt_C",
"L261.StubTech_C",
"L261.GlobalTechCoef_C",
"L261.GlobalTechCost_C",
"L261.GlobalTechShrwt_C",
"L261.GlobalTechCost_C_High",
"L261.GlobalTechShrwt_C_nooffshore",
"L261.DepRsrcCurves_C_high",
"L261.DepRsrcCurves_C_low",
"L261.DepRsrcCurves_C_lowest"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
A61.rsrc_info <- get_data(all_data, "energy/A61.rsrc_info")
A61.sector <- get_data(all_data, "energy/A61.sector")
A61.subsector_logit <- get_data(all_data, "energy/A61.subsector_logit")
A61.subsector_shrwt <- get_data(all_data, "energy/A61.subsector_shrwt")
A61.globaltech_coef <- get_data(all_data, "energy/A61.globaltech_coef")
A61.globaltech_cost <- get_data(all_data, "energy/A61.globaltech_cost")
A61.globaltech_shrwt <- get_data(all_data, "energy/A61.globaltech_shrwt")
L161.RsrcCurves_MtC_R <- get_data(all_data, "L161.RsrcCurves_MtC_R")
# ===================================================
# Silence package notes
. <- available <- capacity.factor <- curr_table <- extractioncost <-
grade <- logit.type <- minicam.energy.input <- minicam.non.energy.input <-
`output-unit` <- `price-unit` <- resource <- resource_type <- share.weight <-
subresource <- subsector <- subsector.name <- supplysector <- technology <-
value <- year <- region <- depresource <- output.unit <- price.unit <-
market <- logit.exponent <- coefficient <- input.cost <- NULL
# A
# Create tables for carbon storage resource information
# A61.rsrc_info provides carbon storage resource info (output unit, price unit, capacity factor, market, etc)
A61.rsrc_info %>%
# Expand table to incorporate GCAM region names (use ID to ensure correct region ordering)
# We will use these specific region names to replace the broad term, regional, in the market column.
repeat_add_columns(GCAM_region_names) %>%
# Reset regional markets to the names of the specific regions
mutate(market = replace(market, market == "regional", region[market == "regional"]),
capacity.factor = as.numeric(capacity.factor)) %>%
rename(output.unit = `output-unit`, price.unit = `price-unit`) ->
L261.rsrc_info
# Split different types of resources into separate tables
# Create table reporting carbon storage information for unlimited resources only
L261.rsrc_info %>%
filter(resource_type == "unlimited-resource") %>%
select(region, unlimited.resource = resource, output.unit, price.unit, market, capacity.factor) ->
L261.UnlimitRsrc # This is a final ouput table.
# Create table reporting carbon storage information for depletable resources only
L261.rsrc_info %>%
filter(resource_type == "depresource") %>%
select(region, depresource = resource, output.unit, price.unit, market) ->
L261.DepRsrc # This is a final ouput table.
# B
# Supply curves of carbon storage resources
# First, define number of decimal places
DIGITS_COST <- 1
# L161.RsrcCurves_MtC_R reports carbon storage resource supply curves by GCAM region.
L161.RsrcCurves_MtC_R %>%
# Match in GCAM region names using region ID
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
mutate(available = round(available, DIGITS_COST)) %>%
select(region, depresource = resource, subresource, grade, available, extractioncost) ->
L261.DepRsrcCurves_C # This is a final output table.
# Calculate three different supply curves of carbon storage resources: high, low, and lowest.
# Multiply the extraction cost by its respective multiplier below.
# Note that the multipliers were created for the SSPs and that high, low, and lowest is the level of CCS use and not cost.
HI_CCS_COST_MULT <- 0.8
LO_CCS_COST_MULT <- 3
LOWEST_CCS_COST_MULT <- 10
# Note that these will produce final output tables.
# High supply curves of carbon storage resources
L261.DepRsrcCurves_C_high <- mutate(L261.DepRsrcCurves_C, extractioncost = extractioncost * HI_CCS_COST_MULT)
# Low supply curves of carbon storage resources
L261.DepRsrcCurves_C_low <- mutate(L261.DepRsrcCurves_C, extractioncost = extractioncost * LO_CCS_COST_MULT)
# Lowest supply curves of carbon storage resources
L261.DepRsrcCurves_C_lowest <- mutate(L261.DepRsrcCurves_C, extractioncost = extractioncost * LOWEST_CCS_COST_MULT)
# C
# Carbon storage sector information
A61.sector %>%
mutate(logit.exponent = as.numeric(logit.exponent)) %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["Supplysector"]], LOGIT_TYPE_COLNAME),
GCAM_region_names = GCAM_region_names) ->
L261.Supplysector_C # This is a final output table.
# D
# Subsector information
# Subsector logit exponents of carbon storage sector
A61.subsector_logit %>%
mutate(logit.exponent = as.numeric(logit.exponent)) %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["SubsectorLogit"]], LOGIT_TYPE_COLNAME),
GCAM_region_names = GCAM_region_names) ->
L261.SubsectorLogit_C # This is a final output table.
# Subsector shareweights of carbon storage sectors
A61.subsector_shrwt %>%
mutate(share.weight = as.numeric(share.weight)) %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["SubsectorShrwtFllt"]], LOGIT_TYPE_COLNAME),
GCAM_region_names = GCAM_region_names) ->
L261.SubsectorShrwtFllt_C # This is a final output table.
# E
# Technology information
# Identification of stub technologies of carbon storage
# A61.globaltech_shrwt reports carbon storage technology shareweights
# Note: assuming that the technology list in the shareweight table includes the full set (any others would default to a 0 shareweight)
A61.globaltech_shrwt %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["Tech"]],
GCAM_region_names = GCAM_region_names) %>%
select(region, supplysector, subsector, stub.technology = technology) ->
L261.StubTech_C # This is a final output table.
# Energy inputs and coefficients of global technologies for carbon storage
# A61.globaltech_coef reports carbon storage global technology coefficients
A61.globaltech_coef %>%
gather_years %>%
# Expand table to include all model base and future years
complete(year = c(year, MODEL_YEARS), nesting(supplysector, subsector, technology, minicam.energy.input)) %>%
# Extrapolate to fill out values for all years
# Rule 2 is used so years outside of min-max range are assigned values from closest data, as opposed to NAs
mutate(coefficient = approx_fun(year, value, rule = 2)) %>%
filter(year %in% MODEL_YEARS) %>% # This will drop 1971
# Assign the columns "sector.name" and "subsector.name", consistent with the location info of a global technology
select(sector.name = supplysector, subsector.name = subsector, technology, year, minicam.energy.input, coefficient) ->
L261.GlobalTechCoef_C # This is a final output table.
# Costs of global technologies
# A61.globaltech_cost reports carbon storage offshore storage cost (1975$/tCO2)
A61.globaltech_cost %>%
gather_years %>%
# Expand table to include all model base and future years
complete(year = c(year, MODEL_YEARS), nesting(supplysector, subsector, technology, minicam.non.energy.input)) %>%
# Extrapolate to fill out values for all years
# Rule 2 is used so years outside of min-max range are assigned values from closest data, as opposed to NAs
mutate(input.cost = approx_fun(year, value, rule = 2)) %>%
filter(year %in% MODEL_YEARS) %>% # This will drop 1971
# Assign the columns "sector.name" and "subsector.name", consistent with the location info of a global technology
select(sector.name = supplysector, subsector.name = subsector, technology, year, minicam.non.energy.input, input.cost) ->
L261.GlobalTechCost_C # This is a final output table.
# High costs of global technologies for carbon storage -- this prices out CCS
L261.GlobalTechCost_C %>%
mutate(subsector.name = "onshore carbon-storage",
technology = "onshore carbon-storage") %>%
bind_rows(L261.GlobalTechCost_C) %>%
# Price out CCS by using storage cost that is very high (i.e., $10,000/tCO2)
mutate(input.cost = 10000) -> # 1975$/tCO2
L261.GlobalTechCost_C_High # This is a final output table.
# Shareweights of global technologies for energy transformation
A61.globaltech_shrwt %>%
gather_years %>%
# Expand table to include all model base and future years
complete(year = c(year, MODEL_YEARS), nesting(supplysector, subsector, technology)) %>%
# Extrapolate to fill out values for all years
# Rule 2 is used so years outside of min-max range are assigned values from closest data, as opposed to NAs
mutate(share.weight = approx_fun(year, value, rule = 2)) %>%
filter(year %in% MODEL_YEARS) %>% # This will drop 1971
# Assign the columns "sector.name" and "subsector.name", consistent with the location info of a global technology
select(sector.name = supplysector, subsector.name = subsector, technology, year, share.weight) ->
L261.GlobalTechShrwt_C # This is a final output table.
# Use zero shareweights for offshore storage
L261.GlobalTechShrwt_C %>%
filter(subsector.name == "offshore carbon-storage") %>%
mutate(share.weight = 0) ->
L261.GlobalTechShrwt_C_nooffshore # This is a final output table.
# ===================================================
L261.DepRsrc %>%
add_title("Carbon storage information") %>%
add_units("Output unit as listed (MtC), price unit as listed (1990$/tC)") %>%
add_comments("Carbon storage resource information was expanded to include GCAM region names") %>%
add_comments("and filtered for only depletable resources") %>%
add_legacy_name("L261.DepRsrc") %>%
add_precursors("common/GCAM_region_names", "energy/A61.rsrc_info") ->
L261.DepRsrc
L261.UnlimitRsrc %>%
add_title("Unlimited carbon storage information") %>%
add_units("Output unit as listed (MtC), price unit as listed (1990$/tC), capacity factor is unitless") %>%
add_comments("Carbon storage resource information was expanded to include GCAM region names") %>%
add_comments("and filtered for only unlimited resources (i.e., offshore)") %>%
add_legacy_name("L261.UnlimitRsrc") %>%
add_precursors("common/GCAM_region_names", "energy/A61.rsrc_info") ->
L261.UnlimitRsrc
L261.DepRsrcCurves_C %>%
add_title("Supply curve of carbon storage resources") %>%
add_units("Available in MtCO2, Extraction Cost in 1990$/tCO2") %>%
add_comments("GCAM region names were added to the resource supply curves generated in level 1") %>%
add_legacy_name("L261.DepRsrcCurves_C") %>%
add_precursors("common/GCAM_region_names", "L161.RsrcCurves_MtC_R") ->
L261.DepRsrcCurves_C
L261.DepRsrcCurves_C_high %>%
add_title("High supply curve of onshore carbon storage resources") %>%
add_units("Available in MtCO2, Extraction Cost in 1990$/tCO2") %>%
add_comments("A multiplier (based on high level of CCS use) was applied to the extraction cost to generate a high supply curve") %>%
add_legacy_name("L261.DepRsrcCurves_C_high") %>%
add_precursors("common/GCAM_region_names", "L161.RsrcCurves_MtC_R") ->
L261.DepRsrcCurves_C_high
L261.DepRsrcCurves_C_low %>%
add_title("Low supply curve of onshore carbon storage resources") %>%
add_units("Available in MtCO2, Extraction Cost in 1990$/tCO2") %>%
add_comments("A multiplier (based on low level of CCS use) was applied to the extraction cost to generate a low supply curve") %>%
add_legacy_name("L261.DepRsrcCurves_C_low") %>%
add_precursors("common/GCAM_region_names", "L161.RsrcCurves_MtC_R") ->
L261.DepRsrcCurves_C_low
L261.DepRsrcCurves_C_lowest %>%
add_title("Lowest supply curve of onshore carbon storage resources") %>%
add_units("Available in MtCO2, Extraction Cost in 1990$/tCO2") %>%
add_comments("A multiplier (based on lowest level of CCS use) was applied to the extraction cost to generate a lowest supply curve") %>%
add_legacy_name("L261.DepRsrcCurves_C_lowest") %>%
add_precursors("common/GCAM_region_names", "L161.RsrcCurves_MtC_R") ->
L261.DepRsrcCurves_C_lowest
L261.Supplysector_C %>%
add_title("Carbon storage sector information") %>%
add_units("Output, input, and price units are as listed; exponent is unitless") %>%
add_comments("Carbon storage sector information was expanded to include GCAM region names") %>%
add_legacy_name("L261.Supplysector_C") %>%
add_precursors("common/GCAM_region_names", "energy/A61.sector") ->
L261.Supplysector_C
L261.SubsectorLogit_C %>%
add_title("Subsector logit exponents of carbon storage sector") %>%
add_units("Unitless") %>%
add_comments("Table on subsector logit exponents was expanded to include GCAM region names") %>%
add_legacy_name("L261.SubsectorLogit_C") %>%
add_precursors("common/GCAM_region_names", "energy/A61.subsector_logit") ->
L261.SubsectorLogit_C
L261.SubsectorShrwtFllt_C %>%
add_title("Subsector shareweights of carbon storage sectors") %>%
add_units("Unitless") %>%
add_comments("Table on subsector shareweights was expanded to include GCAM region names") %>%
add_legacy_name("L261.SubsectorShrwtFllt_C") %>%
add_precursors("common/GCAM_region_names", "energy/A61.subsector_shrwt") ->
L261.SubsectorShrwtFllt_C
L261.StubTech_C %>%
add_title("Identification of stub technologies of carbon storage") %>%
add_units("Not Applicable") %>%
add_comments("Technology list in the global shareweight table for carbon storage was expanded to include GCAM regions") %>%
add_legacy_name("L261.StubTech_C") %>%
add_precursors("common/GCAM_region_names", "energy/A61.globaltech_shrwt") ->
L261.StubTech_C
L261.GlobalTechCoef_C %>%
add_title("Carbon storage global technology coefficients across base model years") %>%
add_units("Unitless") %>%
add_comments("Global technology coefficients were interpolated across all base model years") %>%
add_legacy_name("L261.GlobalTechCoef_C") %>%
add_precursors("energy/A61.globaltech_coef") ->
L261.GlobalTechCoef_C
L261.GlobalTechCost_C %>%
add_title("Carbon storage global technology costs across base model years") %>%
add_units("1975$/tCO2") %>%
add_comments("Global technology coefficients were interpolated across all base model years") %>%
add_legacy_name("L261.GlobalTechCost_C") %>%
add_precursors("energy/A61.globaltech_cost") ->
L261.GlobalTechCost_C
L261.GlobalTechCost_C_High %>%
add_title("Carbon storage global technology costs across base model years (high price scenario)") %>%
add_units("1975$/tCO2") %>%
add_comments("Assigned onshore and offshore carbon storage technologies a high price to price out CCS") %>%
add_legacy_name("L261.GlobalTechCost_C_High") %>%
add_precursors("energy/A61.globaltech_cost") ->
L261.GlobalTechCost_C_High
L261.GlobalTechShrwt_C %>%
add_title("Shareweights of carbon storage technologies across base model years") %>%
add_units("Unitless") %>%
add_comments("Shareweights of global technologies for energy transformation were interpolated across all base model years") %>%
add_legacy_name("L261.GlobalTechShrwt_C") %>%
add_precursors("energy/A61.globaltech_shrwt") ->
L261.GlobalTechShrwt_C
L261.GlobalTechShrwt_C_nooffshore %>%
add_title("Shareweights of offshore carbon storage technologies") %>%
add_units("Unitless") %>%
add_comments("Subset shareweight table for offshore only. Assigned them shareweights of zero") %>%
add_legacy_name("L261.GlobalTechShrwt_C_nooffshore") %>%
add_precursors("energy/A61.globaltech_shrwt") ->
L261.GlobalTechShrwt_C_nooffshore
return_data(L261.DepRsrc, L261.UnlimitRsrc, L261.DepRsrcCurves_C, L261.Supplysector_C, L261.SubsectorLogit_C, L261.SubsectorShrwtFllt_C, L261.StubTech_C, L261.GlobalTechCoef_C, L261.GlobalTechCost_C, L261.GlobalTechShrwt_C, L261.GlobalTechCost_C_High, L261.GlobalTechShrwt_C_nooffshore, L261.DepRsrcCurves_C_high, L261.DepRsrcCurves_C_low, L261.DepRsrcCurves_C_lowest)
} else {
stop("Unknown command")
}
}
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