R/zchunk_L1233.Elec_water.R
In rohmin9122/gcam-korea-release: Build the GCAM-Korea Input Datasets
Defines functions
module_water_L1233.Elec_water
Documented in
module_water_L1233.Elec_water
#' module_water_L1233.Elec_water
#'
#' Water consumption and withdrawals for electricity.
#'
#' @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{L1233.out_EJ_R_elec_F_tech_Yh_cool}, \code{L1233.in_EJ_R_elec_F_tech_Yh_cool}, \code{L1233.wdraw_km3_R_elec}, \code{L1233.wcons_km3_R_elec}, \code{L1233.shrwt_R_elec_cool_Yf}. The corresponding file in the
#' original data system was \code{L1233.Elec_water.R} (water level1).
#' @details Categorizes electricity generating technologies by cooling water type, and computes water withdrawals and consumption.
#' @importFrom assertthat assert_that
#' @importFrom dplyr filter mutate select last
#' @importFrom tidyr gather spread complete fill
#' @author SWDT May 2017
module_water_L1233.Elec_water <- function(command, ...) {
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/iso_GCAM_regID",
FILE = "energy/calibrated_techs",
FILE = "energy/enduse_fuel_aggregation",
"L101.en_bal_EJ_ctry_Si_Fi_Yh_full",
"L1231.in_EJ_R_elec_F_tech_Yh",
"L1231.out_EJ_R_elec_F_tech_Yh",
FILE = "water/A23.CoolingSystemShares_RG3",
FILE = "water/elec_tech_water_map",
FILE = "water/Macknick_elec_water_m3MWh"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L1233.out_EJ_R_elec_F_tech_Yh_cool",
"L1233.in_EJ_R_elec_F_tech_Yh_cool",
"L1233.wdraw_km3_R_elec",
"L1233.wcons_km3_R_elec",
"L1233.shrwt_R_elec_cool_Yf"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
EcYield_kgm2_hi <- EcYield_kgm2_lo <- GCAM_commodity <- GCAM_region_ID <- GLU <-
Irr_Rfd <- LC_bm2_hi <- LC_bm2_lo <- cooling_system <- country_name <- electricity <-
fuel <- gen <- iso <- landshare_hi <- landshare_lo <- level <- output <- output_cool <-
plant_type <- region_GCAM3 <- sector <- share <- technology <- value <-
water_consumption <- water_type <- water_withdrawals <- year <- yield <-
yieldmult_hi <- yieldmult_lo <- NULL # silence package check notes
# Load required inputs
iso_GCAM_regID <- get_data(all_data, "common/iso_GCAM_regID")
calibrated_techs <- get_data(all_data, "energy/calibrated_techs")
enduse_fuel_aggregation <- get_data(all_data, "energy/enduse_fuel_aggregation")
A23.CoolingSystemShares_RG3 <- get_data(all_data, "water/A23.CoolingSystemShares_RG3")
elec_tech_water_map <- get_data(all_data, "water/elec_tech_water_map")
Macknick_elec_water_m3MWh <- get_data(all_data, "water/Macknick_elec_water_m3MWh")
L1231.in_EJ_R_elec_F_tech_Yh <- get_data(all_data, "L1231.in_EJ_R_elec_F_tech_Yh")
L1231.out_EJ_R_elec_F_tech_Yh <- get_data(all_data, "L1231.out_EJ_R_elec_F_tech_Yh")
L101.en_bal_EJ_ctry_Si_Fi_Yh_full <- get_data(all_data, "L101.en_bal_EJ_ctry_Si_Fi_Yh_full")
# ===================================================
## STEP 1. DOWNSCALE WATER COOLING SYSTEM SHARES FROM 14 REGIONS to 201 COUNTRIES
# RENAME INTERMEDIATE FUELS AND AGGREGATE BY UPDATED FUEL TYPE
L101.en_bal_EJ_ctry_Si_Fi_Yh_full %>%
filter(sector == "out_electricity generation") %>%
left_join(select(enduse_fuel_aggregation, fuel, electricity), by = "fuel") %>%
# ^^ non-restrictive join required, since electricity variable has NA for certain fuels
select(-fuel) %>%
rename(fuel = electricity) -> L1233.out_EJ_ctry_elec_Fi_Yh_full
L1233.out_EJ_ctry_elec_Fi_Yh_full %>%
filter(year %in% HISTORICAL_YEARS) %>%
group_by(iso, year, fuel) %>%
summarise(value = sum(value)) %>%
ungroup() %>%
filter(is.na(fuel) == FALSE) %>%
mutate(sector = "electricity generation") -> # << rename sector entries for consistency with other tables
L1233.out_EJ_ctry_elec_F_Yh
# INTERPOLATE A23.CoolingSystemShares_RG3 FOR HISTORICAL YEARS AND HISTORICAL + FUTURE YEARS
A23.CoolingSystemShares_RG3 %>%
gather_years %>%
complete(nesting(region_GCAM3, plant_type, cooling_system, water_type),
year = c(HISTORICAL_YEARS, FUTURE_YEARS)) %>%
filter(year %in% c(HISTORICAL_YEARS, FUTURE_YEARS)) %>% # Written by Jeon (from Original JGCRI-GCAM)
group_by(region_GCAM3, plant_type, cooling_system, water_type) %>%
mutate(value = approx_fun(year, value, rule = 1)) %>%
ungroup() ->
A23.CoolingSystemShares_RG3_LF # << A23.CoolingSystemShares_RG3 in long form and interpolated for all yrs
A23.CoolingSystemShares_RG3_LF %>%
filter(year %in% HISTORICAL_YEARS) ->
A23.CoolingSystemShares_RG3_LF_hist # << ...and interpolated for only historical years
# WRITE OUT REGIONAL LEVEL COOLING INFORMATION TO ALL COUNTRIES...
# ... AND MATCH GCAM region_GCAM3 INTO TIBBLE
elec_tech_water_map %>%
semi_join(calibrated_techs, by = c("sector", "fuel", "technology")) %>%
# ^^ semi_join used to remove rows in elec_tech_water_map that have no matches in calibrated_techs ^^
select(sector, fuel, technology, cooling_system, water_type, plant_type) -> elec_tech_water_map_cal
elec_tech_water_map_cal %>%
repeat_add_columns(select(L1233.out_EJ_ctry_elec_F_Yh, iso) %>% unique()) %>%
left_join_error_no_match(select(iso_GCAM_regID, iso, region_GCAM3), by = "iso") %>%
left_join(A23.CoolingSystemShares_RG3_LF_hist,
by = c("cooling_system", "water_type", "plant_type", "region_GCAM3")) %>%
# ^^ non-restrictive join required as A23 lacks data for "no cooling" plant type
complete(nesting(sector, fuel, technology, cooling_system, water_type, plant_type, iso, region_GCAM3),
year = HISTORICAL_YEARS) %>% # << Fill out all years for "no cooling" plant type
filter(year %in% HISTORICAL_YEARS) %>% # Written by Jeon (from Original JGCRI-GCAM)
mutate(value = if_else(plant_type == "no cooling", 1, value)) %>%
# ^^ Set cooling system share to 1 for technologies with no cooling
rename(share = value) -> L1233.weights_ctry_elec_F_Yh_cool
## STEP 2. MULTIPLY SHARES BY COUNTRY LEVEL GENERATION TO GET ELECTRICITY...
## ... OUTPUT BY GENERATING AND COOLING TECHNOLOGIES
L1233.weights_ctry_elec_F_Yh_cool %>%
left_join(L1233.out_EJ_ctry_elec_F_Yh, by = c("iso", "year", "fuel", "sector")) %>%
# ^^ non-restrictive join required for additional combinations of grouping variables in initial tibble
rename(gen = value) %>%
mutate(output = share * gen) %>%
select(-share, -gen) %>%
replace_na(list(output = 0)) -> L1233.output_ctry_elec_F_Yh_cool
## STEP 3: AGGREGATE COUNTRY-LEVEL DATA TO NEW GCAM REGIONS
# (a) ...WITH COOLING TECHNOLOGIES
L1233.output_ctry_elec_F_Yh_cool %>%
left_join_error_no_match(select(iso_GCAM_regID,-country_name, -region_GCAM3), by = "iso") %>%
group_by(GCAM_region_ID, sector, fuel, technology, cooling_system, water_type, year) %>%
summarise(output = sum(output)) %>%
ungroup() -> L1233.weights_R_elec_F_Yh_cool
# (b) ...WITHOUT COOLING TECHNOLOGIES
L1233.output_ctry_elec_F_Yh_cool %>%
left_join_error_no_match(select(iso_GCAM_regID,-country_name, -region_GCAM3), by = "iso") %>%
group_by(GCAM_region_ID, sector, fuel, technology, year) %>%
summarise(output = sum(output)) %>%
ungroup() -> L1233.weights_R_elec_F_Yh
## STEP 4: MATCH REGIONAL-LEVEL SHARES OF COOLING TECHNOLOGY WITH GENERATION TECHNOLOGY
elec_tech_water_map_cal %>%
repeat_add_columns(unique(select(iso_GCAM_regID, GCAM_region_ID))) %>%
select(GCAM_region_ID, sector, fuel, technology, cooling_system, water_type, plant_type) %>%
left_join(L1233.weights_R_elec_F_Yh_cool,
by = c("GCAM_region_ID", "sector", "fuel", "technology", "cooling_system", "water_type")) %>%
rename(output_cool = output) %>%
left_join(L1233.weights_R_elec_F_Yh,
by = c("GCAM_region_ID", "sector", "fuel", "technology", "year")) %>%
mutate(share = if_else(output + output_cool == 0, NA_real_, output_cool / output)) %>%
# ^^ above used to catch possible NaN and set as NA instead so that tidyr::fill works below
select(-output_cool, -output) %>%
arrange(GCAM_region_ID, sector, fuel, technology, cooling_system, water_type, plant_type, year) %>%
group_by(GCAM_region_ID, sector, fuel, technology, cooling_system, water_type, plant_type) %>%
fill(share, .direction = "up") %>% ungroup() %>%
replace_na(list(share = -1)) ->
L1233.shares_R_elec_F_tech_Yh_cool
## STEP 5: MULTIPLY SHARES BY TECHNOLOGY-LEVEL OUTPUT TO COMPUTE NEW CALIBRATION DATASET
L1233.shares_R_elec_F_tech_Yh_cool %>%
left_join(L1231.out_EJ_R_elec_F_tech_Yh,
by = c("GCAM_region_ID", "sector", "fuel", "technology", "year")) %>%
mutate(value = share * value) %>% select(-share) -> L1233.out_EJ_R_elec_F_tech_Yh_cool
## STEP 6: PARTITION FUEL INPUTS TO ELECTRICITY GENERATION...
## ... USING COOLING-WITHIN-GENERATION TECHNOLOGY SHARES
## NOTE: ASSUMES UNIFORM EFFICIENCY ACROSS ALL COOLING SYSTEM TYPES
L1233.shares_R_elec_F_tech_Yh_cool %>%
filter(fuel %in% L1231.in_EJ_R_elec_F_tech_Yh$fuel) %>%
filter(technology %in% L1231.in_EJ_R_elec_F_tech_Yh$technology) %>%
left_join(L1231.in_EJ_R_elec_F_tech_Yh,
by = c("GCAM_region_ID", "sector", "fuel", "technology", "year")) %>%
mutate(value = share * value) %>% select(-share) -> L1233.in_EJ_R_elec_F_tech_Yh_cool
# STEP 7: MULTIPLY ELECTRICITY GENERATION BY WITHDRAWAL AND CONSUMPTION...
# ... COEFFICIENTS, AND AGGREGATE BY REGION
# WITHDRAWALS
L1233.out_EJ_R_elec_F_tech_Yh_cool %>%
left_join_error_no_match(Macknick_elec_water_m3MWh,
by = c("sector", "fuel", "technology", "cooling_system", "water_type")) %>%
mutate(value = value * water_withdrawals / CONV_MWH_GJ) %>%
select(-water_withdrawals, - water_consumption) -> L1233.wdraw_km3_R_elec_F_tech_Yh_cool
L1233.wdraw_km3_R_elec_F_tech_Yh_cool %>%
group_by(GCAM_region_ID, sector, water_type, year) %>%
summarise(value = sum(value)) %>%
ungroup() %>%
filter(water_type != "none") -> L1233.wdraw_km3_R_elec
# CONSUMPTION
L1233.out_EJ_R_elec_F_tech_Yh_cool %>%
left_join_error_no_match(Macknick_elec_water_m3MWh,
by = c("sector", "fuel", "technology", "cooling_system", "water_type")) %>%
mutate(value = value * water_consumption / CONV_MWH_GJ) %>%
select(-water_withdrawals, - water_consumption) -> L1233.wcons_km3_R_elec_F_tech_Yh_cool
L1233.wcons_km3_R_elec_F_tech_Yh_cool %>%
group_by(GCAM_region_ID, sector, water_type, year) %>%
summarise(value = sum(value)) %>%
ungroup() %>%
filter(water_type != "none") -> L1233.wcons_km3_R_elec
## STEP 8: COMPUTE REGIONAL-LEVEL FUTURE SHARE WEIGHTS...
## ... BASED ON GCAM 3.0, 14-REGION ASSUMPTIONS. NOTE: USES ...
## ... REPRESENTATIVE COUNTRIES RATHER THAN WEIGHTED AVERAGES ...
## ... (COUNTRY WITH MOST ELEC AS THE REPRESENTATIVE)
L1233.out_EJ_ctry_elec_Fi_Yh_full %>%
filter(year == dplyr::last(HISTORICAL_YEARS)) %>%
group_by(iso, GCAM_region_ID) %>%
summarise(value = sum(value)) %>%
arrange(GCAM_region_ID) %>% ungroup() -> L1233.out_EJ_ctry_elec_Yfby
L1233.out_EJ_ctry_elec_Yfby %>%
group_by(GCAM_region_ID) %>%
filter(value == max(value)) %>% ungroup() %>%
left_join_error_no_match(select(iso_GCAM_regID, -country_name),
by = c("iso", "GCAM_region_ID")) -> L1233.R_iso_RG3
## STEP 9: FILL OUT TABLE OF ALL TECHNOLOGIES TO MATCH IN SHARES
elec_tech_water_map %>%
select(sector, fuel, technology, cooling_system, water_type, plant_type) %>%
repeat_add_columns(select(iso_GCAM_regID, GCAM_region_ID) %>% unique()) %>%
arrange(GCAM_region_ID) %>%
left_join(select(L1233.R_iso_RG3, -value, -iso), by = "GCAM_region_ID") %>%
mutate(plant_type = sub("\\ \\(CCS\\)", "", plant_type)) %>%
# ^^ sub out CCS parentheses to allow clean join with A.23, which doesn't classify tech. at this detail
# filter regions in case there are GCAM3 regions that aren't assigned to any regions (e.g., running with a small # of regions)
right_join(filter(A23.CoolingSystemShares_RG3_LF, region_GCAM3 %in% L1233.R_iso_RG3$region_GCAM3),
by = c("cooling_system", "water_type", "plant_type", "region_GCAM3")) %>%
select(-region_GCAM3, -plant_type) ->
L1233.shrwt_R_elec_cool_Yf
## OUTPUTS
L1233.out_EJ_R_elec_F_tech_Yh_cool %>%
add_title("Electricity output by region, fuel, technology, cooling system, and water type") %>%
add_units("EJ") %>%
add_comments("Computed by multiplying shares by technology-level output") %>%
add_legacy_name("L1233.out_EJ_R_elec_F_tech_Yh_cool") %>%
add_precursors("common/iso_GCAM_regID",
"energy/calibrated_techs",
"energy/enduse_fuel_aggregation",
"L101.en_bal_EJ_ctry_Si_Fi_Yh_full",
"L1231.in_EJ_R_elec_F_tech_Yh",
"L1231.out_EJ_R_elec_F_tech_Yh",
"water/A23.CoolingSystemShares_RG3",
"water/elec_tech_water_map") ->
L1233.out_EJ_R_elec_F_tech_Yh_cool
L1233.in_EJ_R_elec_F_tech_Yh_cool %>%
add_title("Fuel inputs to electricity generation by region, fuel, technology, cooling system, and water type") %>%
add_units("EJ") %>%
add_comments("Computed by multiplying shares by technology-level input") %>%
add_legacy_name("L1233.in_EJ_R_elec_F_tech_Yh_cool") %>%
add_precursors("common/iso_GCAM_regID",
"energy/calibrated_techs",
"energy/enduse_fuel_aggregation",
"L101.en_bal_EJ_ctry_Si_Fi_Yh_full",
"L1231.in_EJ_R_elec_F_tech_Yh",
"L1231.out_EJ_R_elec_F_tech_Yh",
"water/A23.CoolingSystemShares_RG3",
"water/elec_tech_water_map") ->
L1233.in_EJ_R_elec_F_tech_Yh_cool
L1233.wdraw_km3_R_elec %>%
add_title("Water withdrawals for electricity generation by region and water type") %>%
add_units("km^3") %>%
add_comments("Computed by multiplying generation by water withdrawal coefficients") %>%
add_legacy_name("L1233.wdraw_km3_R_elec") %>%
add_precursors("common/iso_GCAM_regID",
"energy/calibrated_techs",
"energy/enduse_fuel_aggregation",
"L101.en_bal_EJ_ctry_Si_Fi_Yh_full",
"L1231.out_EJ_R_elec_F_tech_Yh",
"water/A23.CoolingSystemShares_RG3",
"water/elec_tech_water_map",
"water/Macknick_elec_water_m3MWh") ->
L1233.wdraw_km3_R_elec
L1233.wcons_km3_R_elec %>%
add_title("Water consumption for electricity generation by region and water type") %>%
add_units("km^3") %>%
add_comments("Computed by multiplying generation by water consumption coefficients") %>%
add_legacy_name("L1233.wcons_km3_R_elec") %>%
add_precursors("common/iso_GCAM_regID",
"energy/calibrated_techs",
"energy/enduse_fuel_aggregation",
"L101.en_bal_EJ_ctry_Si_Fi_Yh_full",
"L1231.out_EJ_R_elec_F_tech_Yh",
"water/A23.CoolingSystemShares_RG3",
"water/elec_tech_water_map",
"water/Macknick_elec_water_m3MWh") ->
L1233.wcons_km3_R_elec
L1233.shrwt_R_elec_cool_Yf %>%
add_title("Future cooling system shareweights by region, electric sector, and technology ") %>%
add_units("Unitless") %>%
add_comments("Filled out using cooling shares table") %>%
add_legacy_name("L1233.shrwt_R_elec_cool_Yf") %>%
add_precursors("common/iso_GCAM_regID",
"water/A23.CoolingSystemShares_RG3",
"water/elec_tech_water_map") ->
L1233.shrwt_R_elec_cool_Yf
return_data(L1233.out_EJ_R_elec_F_tech_Yh_cool, L1233.in_EJ_R_elec_F_tech_Yh_cool, L1233.wdraw_km3_R_elec, L1233.wcons_km3_R_elec, L1233.shrwt_R_elec_cool_Yf)
} 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_water_L1233.Elec_water
Documented in module_water_L1233.Elec_water
#' module_water_L1233.Elec_water
#'
#' Water consumption and withdrawals for electricity.
#'
#' @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{L1233.out_EJ_R_elec_F_tech_Yh_cool}, \code{L1233.in_EJ_R_elec_F_tech_Yh_cool}, \code{L1233.wdraw_km3_R_elec}, \code{L1233.wcons_km3_R_elec}, \code{L1233.shrwt_R_elec_cool_Yf}. The corresponding file in the
#' original data system was \code{L1233.Elec_water.R} (water level1).
#' @details Categorizes electricity generating technologies by cooling water type, and computes water withdrawals and consumption.
#' @importFrom assertthat assert_that
#' @importFrom dplyr filter mutate select last
#' @importFrom tidyr gather spread complete fill
#' @author SWDT May 2017
module_water_L1233.Elec_water <- function(command, ...) {
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/iso_GCAM_regID",
FILE = "energy/calibrated_techs",
FILE = "energy/enduse_fuel_aggregation",
"L101.en_bal_EJ_ctry_Si_Fi_Yh_full",
"L1231.in_EJ_R_elec_F_tech_Yh",
"L1231.out_EJ_R_elec_F_tech_Yh",
FILE = "water/A23.CoolingSystemShares_RG3",
FILE = "water/elec_tech_water_map",
FILE = "water/Macknick_elec_water_m3MWh"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L1233.out_EJ_R_elec_F_tech_Yh_cool",
"L1233.in_EJ_R_elec_F_tech_Yh_cool",
"L1233.wdraw_km3_R_elec",
"L1233.wcons_km3_R_elec",
"L1233.shrwt_R_elec_cool_Yf"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
EcYield_kgm2_hi <- EcYield_kgm2_lo <- GCAM_commodity <- GCAM_region_ID <- GLU <-
Irr_Rfd <- LC_bm2_hi <- LC_bm2_lo <- cooling_system <- country_name <- electricity <-
fuel <- gen <- iso <- landshare_hi <- landshare_lo <- level <- output <- output_cool <-
plant_type <- region_GCAM3 <- sector <- share <- technology <- value <-
water_consumption <- water_type <- water_withdrawals <- year <- yield <-
yieldmult_hi <- yieldmult_lo <- NULL # silence package check notes
# Load required inputs
iso_GCAM_regID <- get_data(all_data, "common/iso_GCAM_regID")
calibrated_techs <- get_data(all_data, "energy/calibrated_techs")
enduse_fuel_aggregation <- get_data(all_data, "energy/enduse_fuel_aggregation")
A23.CoolingSystemShares_RG3 <- get_data(all_data, "water/A23.CoolingSystemShares_RG3")
elec_tech_water_map <- get_data(all_data, "water/elec_tech_water_map")
Macknick_elec_water_m3MWh <- get_data(all_data, "water/Macknick_elec_water_m3MWh")
L1231.in_EJ_R_elec_F_tech_Yh <- get_data(all_data, "L1231.in_EJ_R_elec_F_tech_Yh")
L1231.out_EJ_R_elec_F_tech_Yh <- get_data(all_data, "L1231.out_EJ_R_elec_F_tech_Yh")
L101.en_bal_EJ_ctry_Si_Fi_Yh_full <- get_data(all_data, "L101.en_bal_EJ_ctry_Si_Fi_Yh_full")
# ===================================================
## STEP 1. DOWNSCALE WATER COOLING SYSTEM SHARES FROM 14 REGIONS to 201 COUNTRIES
# RENAME INTERMEDIATE FUELS AND AGGREGATE BY UPDATED FUEL TYPE
L101.en_bal_EJ_ctry_Si_Fi_Yh_full %>%
filter(sector == "out_electricity generation") %>%
left_join(select(enduse_fuel_aggregation, fuel, electricity), by = "fuel") %>%
# ^^ non-restrictive join required, since electricity variable has NA for certain fuels
select(-fuel) %>%
rename(fuel = electricity) -> L1233.out_EJ_ctry_elec_Fi_Yh_full
L1233.out_EJ_ctry_elec_Fi_Yh_full %>%
filter(year %in% HISTORICAL_YEARS) %>%
group_by(iso, year, fuel) %>%
summarise(value = sum(value)) %>%
ungroup() %>%
filter(is.na(fuel) == FALSE) %>%
mutate(sector = "electricity generation") -> # << rename sector entries for consistency with other tables
L1233.out_EJ_ctry_elec_F_Yh
# INTERPOLATE A23.CoolingSystemShares_RG3 FOR HISTORICAL YEARS AND HISTORICAL + FUTURE YEARS
A23.CoolingSystemShares_RG3 %>%
gather_years %>%
complete(nesting(region_GCAM3, plant_type, cooling_system, water_type),
year = c(HISTORICAL_YEARS, FUTURE_YEARS)) %>%
filter(year %in% c(HISTORICAL_YEARS, FUTURE_YEARS)) %>% # Written by Jeon (from Original JGCRI-GCAM)
group_by(region_GCAM3, plant_type, cooling_system, water_type) %>%
mutate(value = approx_fun(year, value, rule = 1)) %>%
ungroup() ->
A23.CoolingSystemShares_RG3_LF # << A23.CoolingSystemShares_RG3 in long form and interpolated for all yrs
A23.CoolingSystemShares_RG3_LF %>%
filter(year %in% HISTORICAL_YEARS) ->
A23.CoolingSystemShares_RG3_LF_hist # << ...and interpolated for only historical years
# WRITE OUT REGIONAL LEVEL COOLING INFORMATION TO ALL COUNTRIES...
# ... AND MATCH GCAM region_GCAM3 INTO TIBBLE
elec_tech_water_map %>%
semi_join(calibrated_techs, by = c("sector", "fuel", "technology")) %>%
# ^^ semi_join used to remove rows in elec_tech_water_map that have no matches in calibrated_techs ^^
select(sector, fuel, technology, cooling_system, water_type, plant_type) -> elec_tech_water_map_cal
elec_tech_water_map_cal %>%
repeat_add_columns(select(L1233.out_EJ_ctry_elec_F_Yh, iso) %>% unique()) %>%
left_join_error_no_match(select(iso_GCAM_regID, iso, region_GCAM3), by = "iso") %>%
left_join(A23.CoolingSystemShares_RG3_LF_hist,
by = c("cooling_system", "water_type", "plant_type", "region_GCAM3")) %>%
# ^^ non-restrictive join required as A23 lacks data for "no cooling" plant type
complete(nesting(sector, fuel, technology, cooling_system, water_type, plant_type, iso, region_GCAM3),
year = HISTORICAL_YEARS) %>% # << Fill out all years for "no cooling" plant type
filter(year %in% HISTORICAL_YEARS) %>% # Written by Jeon (from Original JGCRI-GCAM)
mutate(value = if_else(plant_type == "no cooling", 1, value)) %>%
# ^^ Set cooling system share to 1 for technologies with no cooling
rename(share = value) -> L1233.weights_ctry_elec_F_Yh_cool
## STEP 2. MULTIPLY SHARES BY COUNTRY LEVEL GENERATION TO GET ELECTRICITY...
## ... OUTPUT BY GENERATING AND COOLING TECHNOLOGIES
L1233.weights_ctry_elec_F_Yh_cool %>%
left_join(L1233.out_EJ_ctry_elec_F_Yh, by = c("iso", "year", "fuel", "sector")) %>%
# ^^ non-restrictive join required for additional combinations of grouping variables in initial tibble
rename(gen = value) %>%
mutate(output = share * gen) %>%
select(-share, -gen) %>%
replace_na(list(output = 0)) -> L1233.output_ctry_elec_F_Yh_cool
## STEP 3: AGGREGATE COUNTRY-LEVEL DATA TO NEW GCAM REGIONS
# (a) ...WITH COOLING TECHNOLOGIES
L1233.output_ctry_elec_F_Yh_cool %>%
left_join_error_no_match(select(iso_GCAM_regID,-country_name, -region_GCAM3), by = "iso") %>%
group_by(GCAM_region_ID, sector, fuel, technology, cooling_system, water_type, year) %>%
summarise(output = sum(output)) %>%
ungroup() -> L1233.weights_R_elec_F_Yh_cool
# (b) ...WITHOUT COOLING TECHNOLOGIES
L1233.output_ctry_elec_F_Yh_cool %>%
left_join_error_no_match(select(iso_GCAM_regID,-country_name, -region_GCAM3), by = "iso") %>%
group_by(GCAM_region_ID, sector, fuel, technology, year) %>%
summarise(output = sum(output)) %>%
ungroup() -> L1233.weights_R_elec_F_Yh
## STEP 4: MATCH REGIONAL-LEVEL SHARES OF COOLING TECHNOLOGY WITH GENERATION TECHNOLOGY
elec_tech_water_map_cal %>%
repeat_add_columns(unique(select(iso_GCAM_regID, GCAM_region_ID))) %>%
select(GCAM_region_ID, sector, fuel, technology, cooling_system, water_type, plant_type) %>%
left_join(L1233.weights_R_elec_F_Yh_cool,
by = c("GCAM_region_ID", "sector", "fuel", "technology", "cooling_system", "water_type")) %>%
rename(output_cool = output) %>%
left_join(L1233.weights_R_elec_F_Yh,
by = c("GCAM_region_ID", "sector", "fuel", "technology", "year")) %>%
mutate(share = if_else(output + output_cool == 0, NA_real_, output_cool / output)) %>%
# ^^ above used to catch possible NaN and set as NA instead so that tidyr::fill works below
select(-output_cool, -output) %>%
arrange(GCAM_region_ID, sector, fuel, technology, cooling_system, water_type, plant_type, year) %>%
group_by(GCAM_region_ID, sector, fuel, technology, cooling_system, water_type, plant_type) %>%
fill(share, .direction = "up") %>% ungroup() %>%
replace_na(list(share = -1)) ->
L1233.shares_R_elec_F_tech_Yh_cool
## STEP 5: MULTIPLY SHARES BY TECHNOLOGY-LEVEL OUTPUT TO COMPUTE NEW CALIBRATION DATASET
L1233.shares_R_elec_F_tech_Yh_cool %>%
left_join(L1231.out_EJ_R_elec_F_tech_Yh,
by = c("GCAM_region_ID", "sector", "fuel", "technology", "year")) %>%
mutate(value = share * value) %>% select(-share) -> L1233.out_EJ_R_elec_F_tech_Yh_cool
## STEP 6: PARTITION FUEL INPUTS TO ELECTRICITY GENERATION...
## ... USING COOLING-WITHIN-GENERATION TECHNOLOGY SHARES
## NOTE: ASSUMES UNIFORM EFFICIENCY ACROSS ALL COOLING SYSTEM TYPES
L1233.shares_R_elec_F_tech_Yh_cool %>%
filter(fuel %in% L1231.in_EJ_R_elec_F_tech_Yh$fuel) %>%
filter(technology %in% L1231.in_EJ_R_elec_F_tech_Yh$technology) %>%
left_join(L1231.in_EJ_R_elec_F_tech_Yh,
by = c("GCAM_region_ID", "sector", "fuel", "technology", "year")) %>%
mutate(value = share * value) %>% select(-share) -> L1233.in_EJ_R_elec_F_tech_Yh_cool
# STEP 7: MULTIPLY ELECTRICITY GENERATION BY WITHDRAWAL AND CONSUMPTION...
# ... COEFFICIENTS, AND AGGREGATE BY REGION
# WITHDRAWALS
L1233.out_EJ_R_elec_F_tech_Yh_cool %>%
left_join_error_no_match(Macknick_elec_water_m3MWh,
by = c("sector", "fuel", "technology", "cooling_system", "water_type")) %>%
mutate(value = value * water_withdrawals / CONV_MWH_GJ) %>%
select(-water_withdrawals, - water_consumption) -> L1233.wdraw_km3_R_elec_F_tech_Yh_cool
L1233.wdraw_km3_R_elec_F_tech_Yh_cool %>%
group_by(GCAM_region_ID, sector, water_type, year) %>%
summarise(value = sum(value)) %>%
ungroup() %>%
filter(water_type != "none") -> L1233.wdraw_km3_R_elec
# CONSUMPTION
L1233.out_EJ_R_elec_F_tech_Yh_cool %>%
left_join_error_no_match(Macknick_elec_water_m3MWh,
by = c("sector", "fuel", "technology", "cooling_system", "water_type")) %>%
mutate(value = value * water_consumption / CONV_MWH_GJ) %>%
select(-water_withdrawals, - water_consumption) -> L1233.wcons_km3_R_elec_F_tech_Yh_cool
L1233.wcons_km3_R_elec_F_tech_Yh_cool %>%
group_by(GCAM_region_ID, sector, water_type, year) %>%
summarise(value = sum(value)) %>%
ungroup() %>%
filter(water_type != "none") -> L1233.wcons_km3_R_elec
## STEP 8: COMPUTE REGIONAL-LEVEL FUTURE SHARE WEIGHTS...
## ... BASED ON GCAM 3.0, 14-REGION ASSUMPTIONS. NOTE: USES ...
## ... REPRESENTATIVE COUNTRIES RATHER THAN WEIGHTED AVERAGES ...
## ... (COUNTRY WITH MOST ELEC AS THE REPRESENTATIVE)
L1233.out_EJ_ctry_elec_Fi_Yh_full %>%
filter(year == dplyr::last(HISTORICAL_YEARS)) %>%
group_by(iso, GCAM_region_ID) %>%
summarise(value = sum(value)) %>%
arrange(GCAM_region_ID) %>% ungroup() -> L1233.out_EJ_ctry_elec_Yfby
L1233.out_EJ_ctry_elec_Yfby %>%
group_by(GCAM_region_ID) %>%
filter(value == max(value)) %>% ungroup() %>%
left_join_error_no_match(select(iso_GCAM_regID, -country_name),
by = c("iso", "GCAM_region_ID")) -> L1233.R_iso_RG3
## STEP 9: FILL OUT TABLE OF ALL TECHNOLOGIES TO MATCH IN SHARES
elec_tech_water_map %>%
select(sector, fuel, technology, cooling_system, water_type, plant_type) %>%
repeat_add_columns(select(iso_GCAM_regID, GCAM_region_ID) %>% unique()) %>%
arrange(GCAM_region_ID) %>%
left_join(select(L1233.R_iso_RG3, -value, -iso), by = "GCAM_region_ID") %>%
mutate(plant_type = sub("\\ \\(CCS\\)", "", plant_type)) %>%
# ^^ sub out CCS parentheses to allow clean join with A.23, which doesn't classify tech. at this detail
# filter regions in case there are GCAM3 regions that aren't assigned to any regions (e.g., running with a small # of regions)
right_join(filter(A23.CoolingSystemShares_RG3_LF, region_GCAM3 %in% L1233.R_iso_RG3$region_GCAM3),
by = c("cooling_system", "water_type", "plant_type", "region_GCAM3")) %>%
select(-region_GCAM3, -plant_type) ->
L1233.shrwt_R_elec_cool_Yf
## OUTPUTS
L1233.out_EJ_R_elec_F_tech_Yh_cool %>%
add_title("Electricity output by region, fuel, technology, cooling system, and water type") %>%
add_units("EJ") %>%
add_comments("Computed by multiplying shares by technology-level output") %>%
add_legacy_name("L1233.out_EJ_R_elec_F_tech_Yh_cool") %>%
add_precursors("common/iso_GCAM_regID",
"energy/calibrated_techs",
"energy/enduse_fuel_aggregation",
"L101.en_bal_EJ_ctry_Si_Fi_Yh_full",
"L1231.in_EJ_R_elec_F_tech_Yh",
"L1231.out_EJ_R_elec_F_tech_Yh",
"water/A23.CoolingSystemShares_RG3",
"water/elec_tech_water_map") ->
L1233.out_EJ_R_elec_F_tech_Yh_cool
L1233.in_EJ_R_elec_F_tech_Yh_cool %>%
add_title("Fuel inputs to electricity generation by region, fuel, technology, cooling system, and water type") %>%
add_units("EJ") %>%
add_comments("Computed by multiplying shares by technology-level input") %>%
add_legacy_name("L1233.in_EJ_R_elec_F_tech_Yh_cool") %>%
add_precursors("common/iso_GCAM_regID",
"energy/calibrated_techs",
"energy/enduse_fuel_aggregation",
"L101.en_bal_EJ_ctry_Si_Fi_Yh_full",
"L1231.in_EJ_R_elec_F_tech_Yh",
"L1231.out_EJ_R_elec_F_tech_Yh",
"water/A23.CoolingSystemShares_RG3",
"water/elec_tech_water_map") ->
L1233.in_EJ_R_elec_F_tech_Yh_cool
L1233.wdraw_km3_R_elec %>%
add_title("Water withdrawals for electricity generation by region and water type") %>%
add_units("km^3") %>%
add_comments("Computed by multiplying generation by water withdrawal coefficients") %>%
add_legacy_name("L1233.wdraw_km3_R_elec") %>%
add_precursors("common/iso_GCAM_regID",
"energy/calibrated_techs",
"energy/enduse_fuel_aggregation",
"L101.en_bal_EJ_ctry_Si_Fi_Yh_full",
"L1231.out_EJ_R_elec_F_tech_Yh",
"water/A23.CoolingSystemShares_RG3",
"water/elec_tech_water_map",
"water/Macknick_elec_water_m3MWh") ->
L1233.wdraw_km3_R_elec
L1233.wcons_km3_R_elec %>%
add_title("Water consumption for electricity generation by region and water type") %>%
add_units("km^3") %>%
add_comments("Computed by multiplying generation by water consumption coefficients") %>%
add_legacy_name("L1233.wcons_km3_R_elec") %>%
add_precursors("common/iso_GCAM_regID",
"energy/calibrated_techs",
"energy/enduse_fuel_aggregation",
"L101.en_bal_EJ_ctry_Si_Fi_Yh_full",
"L1231.out_EJ_R_elec_F_tech_Yh",
"water/A23.CoolingSystemShares_RG3",
"water/elec_tech_water_map",
"water/Macknick_elec_water_m3MWh") ->
L1233.wcons_km3_R_elec
L1233.shrwt_R_elec_cool_Yf %>%
add_title("Future cooling system shareweights by region, electric sector, and technology ") %>%
add_units("Unitless") %>%
add_comments("Filled out using cooling shares table") %>%
add_legacy_name("L1233.shrwt_R_elec_cool_Yf") %>%
add_precursors("common/iso_GCAM_regID",
"water/A23.CoolingSystemShares_RG3",
"water/elec_tech_water_map") ->
L1233.shrwt_R_elec_cool_Yf
return_data(L1233.out_EJ_R_elec_F_tech_Yh_cool, L1233.in_EJ_R_elec_F_tech_Yh_cool, L1233.wdraw_km3_R_elec, L1233.wcons_km3_R_elec, L1233.shrwt_R_elec_cool_Yf)
} else {
stop("Unknown command")
}
}
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