R/zchunk_LA2233.elec_segments_water_USA.R
In JGCRI/gcamdata: Build the GCAM Input Datasets
Defines functions
module_gcamusa_LA2233.elec_segments_water_USA
Documented in
module_gcamusa_LA2233.elec_segments_water_USA
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_gcamusa_LA2233.elec_segments_water_USA
#'
#' Generates GCAM-USA model inputs for multiple load segments electricity sector and cooling systems by state.
#'
#' @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{L2233.GlobalTechEff_elecS_cool_USA}, \code{L2233.GlobalTechShrwt_elecS_cool_USA}, \code{L2233.GlobalTechProfitShutdown_elecS_cool_USA},
#' \code{L2233.GlobalTechOMvar_elecS_cool_USA}, \code{L2233.GlobalTechOMfixed_elecS_cool_USA}, \code{L2233.GlobalTechCapital_elecS_USA}, \code{L2233.GlobalTechCapital_elecS_cool_USA},
#' \code{L2233.GlobalTechCapFac_elecS_cool_USA}, \code{L2233.GlobalTechSCurve_elecS_cool_USA}, \code{L2233.GlobalTechCoef_elecS_cool_USA}, \code{L2233.GlobalTechCapture_elecS_cool_USA},
#' \code{L2233.GlobalTechLifetime_elecS_cool_USA}, \code{L2233.AvgFossilEffKeyword_elecS_cool_USA}, \code{L2233.GlobalIntTechBackup_elecS_cool_USA}, \code{L2233.GlobalIntTechCapital_elecS_USA},
#' \code{L2233.GlobalIntTechCapital_elecS_cool_USA}, \code{L2233.GlobalIntTechEff_elecS_USA}, \code{L2233.GlobalIntTechEff_elecS_cool_USA}, \code{L2233.GlobalIntTechLifetime_elecS_cool_USA},
#' \code{L2233.GlobalIntTechOMfixed_elecS_cool_USA}, \code{L2233.GlobalIntTechOMvar_elecS_cool_USA}, \code{L2233.GlobalIntTechShrwt_elecS_cool_USA}, \code{L2233.GlobalIntTechCoef_elecS_cool_USA},
#' \code{L2233.PrimaryRenewKeyword_elecS_cool_USA}, \code{L2233.PrimaryRenewKeywordInt_elecS_cool_USA}, \code{L2233.StubTechEff_elecS_cool_USA}, \code{L2233.StubTechCoef_elecS_cool_USA},
#' \code{L2233.StubTechMarket_elecS_cool_USA}, \code{L2233.StubTechProd_elecS_cool_USA}, \code{L2233.StubTechSCurve_elecS_cool_USA}, \code{L2233.StubTechCapFactor_elecS_solar_USA},
#' \code{L2233.StubTechCapFactor_elecS_wind_USA}, \code{L2233.StubTechElecMarket_backup_elecS_cool_USA}, \code{L2233.StubTechFixOut_elecS_cool_USA}, \code{L2233.StubTechFixOut_hydro_elecS_cool_USA},
#' \code{L2233.StubTechMarket_backup_elecS_cool_USA}, \code{L2233.StubTechProfitShutdown_elecS_cool_USA}, \code{L2233.StubTechShrwt_elecS_cool_USA}, \code{L2233.StubTechInterp_elecS_cool_USA},
#' \code{L2233.StubTechCost_offshore_wind_elecS_cool_USA}, \code{L2233.SubsectorLogit_elecS_USA}, \code{L2233.SubsectorLogit_elecS_cool_USA}, \code{L2233.SubsectorShrwt_elecS_USA},
#' \code{L2233.SubsectorShrwt_elecS_cool_USA}, \code{L2233.SubsectorShrwtInterp_elecS_USA}, \code{L2233.SubsectorShrwtInterpTo_elecS_USA}, \code{L2233.Supplysector_elecS_cool_USA}.
#' The corresponding file in the original data system was \code{LA2233.electricity_water_USA} (gcam-usa level2)
#' @details This chunk generates input files to create an electricity generation sector with multiple load segments
#' for each state and creates the demand by load, fuel, power plant, and cooling system type.
#' @importFrom assertthat assert_that
#' @importFrom dplyr anti_join distinct filter if_else mutate select semi_join summarise_if bind_rows
#' @importFrom tidyr complete nesting replace_na
#' @author NTG May 2020
module_gcamusa_LA2233.elec_segments_water_USA <- function(command, ...) {
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "gcam-usa/A23.elecS_tech_mapping_cool",
FILE = "gcam-usa/elec_tech_water_map",
FILE = "gcam-usa/A23.elecS_tech_mapping_cool_shares_fut",
FILE = "gcam-usa/usa_seawater_states_basins",
"L1233.out_EJ_state_elec_F_tech_cool",
"L2233.GlobalTechEff_elec_cool",
"L2233.GlobalTechShrwt_elec_cool",
"L2233.GlobalTechProfitShutdown_elec_cool",
"L2233.GlobalTechCapital_elec_cool",
"L2233.GlobalTechCapital_elecPassthru",
"L2233.GlobalTechCoef_elec_cool",
"L2233.GlobalIntTechCapital_elec_cool",
"L2233.GlobalIntTechEff_elec_cool",
"L2233.GlobalIntTechCoef_elec_cool",
"L2234.AvgFossilEffKeyword_elecS_USA",
"L2234.GlobalIntTechBackup_elecS_USA",
"L2234.GlobalIntTechCapital_elecS_USA",
"L2234.GlobalIntTechEff_elecS_USA",
"L2234.GlobalIntTechLifetime_elecS_USA",
"L2234.GlobalIntTechOMfixed_elecS_USA",
"L2234.GlobalIntTechOMvar_elecS_USA",
"L2234.GlobalIntTechShrwt_elecS_USA",
"L2234.GlobalTechCapFac_elecS_USA",
"L2234.GlobalTechCapital_elecS_USA",
"L2234.GlobalTechCapture_elecS_USA",
"L2234.GlobalTechEff_elecS_USA",
"L2234.GlobalTechLifetime_elecS_USA",
"L2234.GlobalTechOMfixed_elecS_USA",
"L2234.GlobalTechOMvar_elecS_USA",
"L2234.GlobalTechProfitShutdown_elecS_USA",
"L2234.GlobalTechSCurve_elecS_USA",
"L2234.GlobalTechShrwt_elecS_USA",
"L2234.PrimaryRenewKeyword_elecS_USA",
"L2234.PrimaryRenewKeywordInt_elecS_USA",
"L2234.StubTechCapFactor_elecS_solar_USA",
"L2234.StubTechCapFactor_elecS_wind_USA",
"L2234.StubTechEff_elecS_USA",
"L2234.StubTechElecMarket_backup_elecS_USA",
"L2234.StubTechFixOut_elecS_USA",
"L2234.StubTechFixOut_hydro_elecS_USA",
"L2234.StubTechMarket_backup_elecS_USA",
"L2234.StubTechMarket_elecS_USA",
"L2234.StubTechProd_elecS_USA",
"L2234.SubsectorLogit_elecS_USA",
"L2234.SubsectorShrwt_elecS_USA",
"L2234.SubsectorShrwtInterp_elecS_USA",
"L2234.SubsectorShrwtInterpTo_elecS_USA",
"L2234.Supplysector_elecS_USA",
"L2234.StubTechCost_offshore_wind_elecS_USA",
"L2241.GlobalTechCapFac_elec_coalret_USA",
"L2241.GlobalTechCapital_elec_coalret_USA",
"L2241.GlobalTechEff_elec_coalret_USA",
"L2241.GlobalTechOMfixed_elec_coalret_USA",
"L2241.GlobalTechOMvar_elec_coalret_USA",
"L2241.GlobalTechProfitShutdown_elec_coalret_USA",
"L2241.GlobalTechShrwt_elec_coalret_USA",
"L2241.StubTechEff_elec_coalret_USA",
"L2241.StubTechMarket_elec_coalret_USA",
"L2241.StubTechProd_elec_coalret_USA",
"L2241.StubTechSCurve_elec_coalret_USA",
"L2241.GlobalTechCapFac_coal_vintage_USA",
"L2241.GlobalTechCapital_coal_vintage_USA",
"L2241.GlobalTechEff_coal_vintage_USA",
"L2241.GlobalTechOMfixed_coal_vintage_USA",
"L2241.GlobalTechOMvar_coal_vintage_USA",
"L2241.GlobalTechShrwt_coal_vintage_USA",
"L2241.StubTechEff_coal_vintage_USA",
"L2241.StubTechMarket_coal_vintage_USA",
"L2241.StubTechProd_coal_vintage_USA",
"L2241.StubTechProfitShutdown_coal_vintage_USA",
"L2241.StubTechSCurve_coal_vintage_USA"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L2233.GlobalTechEff_elecS_cool_USA",
"L2233.GlobalTechShrwt_elecS_cool_USA",
"L2233.GlobalTechProfitShutdown_elecS_cool_USA",
"L2233.GlobalTechOMvar_elecS_cool_USA",
"L2233.GlobalTechOMfixed_elecS_cool_USA",
"L2233.GlobalTechCapital_elecS_USA",
"L2233.GlobalTechCapital_elecS_cool_USA",
"L2233.GlobalTechCapFac_elecS_cool_USA",
"L2233.GlobalTechSCurve_elecS_cool_USA",
"L2233.GlobalTechCoef_elecS_cool_USA",
"L2233.GlobalTechCapture_elecS_cool_USA",
"L2233.GlobalTechLifetime_elecS_cool_USA",
"L2233.AvgFossilEffKeyword_elecS_cool_USA",
"L2233.GlobalIntTechBackup_elecS_cool_USA",
"L2233.GlobalIntTechCapital_elecS_USA",
"L2233.GlobalIntTechCapital_elecS_cool_USA",
"L2233.GlobalIntTechEff_elecS_USA",
"L2233.GlobalIntTechEff_elecS_cool_USA",
"L2233.GlobalIntTechLifetime_elecS_cool_USA",
"L2233.GlobalIntTechOMfixed_elecS_cool_USA",
"L2233.GlobalIntTechOMvar_elecS_cool_USA",
"L2233.GlobalIntTechShrwt_elecS_cool_USA",
"L2233.GlobalIntTechCoef_elecS_cool_USA",
"L2233.PrimaryRenewKeyword_elecS_cool_USA",
"L2233.PrimaryRenewKeywordInt_elecS_cool_USA",
"L2233.StubTechEff_elecS_cool_USA",
"L2233.StubTechCoef_elecS_cool_USA",
"L2233.StubTechMarket_elecS_cool_USA",
"L2233.StubTechProd_elecS_cool_USA",
"L2233.StubTechSCurve_elecS_cool_USA",
"L2233.StubTechCapFactor_elecS_solar_USA",
"L2233.StubTechCapFactor_elecS_wind_USA",
"L2233.StubTechElecMarket_backup_elecS_cool_USA",
"L2233.StubTechFixOut_elecS_cool_USA",
"L2233.StubTechFixOut_hydro_elecS_cool_USA",
"L2233.StubTechMarket_backup_elecS_cool_USA",
"L2233.StubTechProfitShutdown_elecS_cool_USA",
"L2233.StubTechShrwt_elecS_cool_USA",
"L2233.StubTechInterp_elecS_cool_USA",
"L2233.StubTechCost_offshore_wind_elecS_cool_USA",
"L2233.SubsectorLogit_elecS_USA",
"L2233.SubsectorLogit_elecS_cool_USA",
"L2233.SubsectorShrwt_elecS_USA",
"L2233.SubsectorShrwt_elecS_cool_USA",
"L2233.SubsectorShrwtInterp_elecS_USA",
"L2233.SubsectorShrwtInterpTo_elecS_USA",
"L2233.Supplysector_elecS_cool_USA"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
region<- supplysector <- subsector <- technology <- year <- minicam.energy.input <-
coefficient<- market.name <- Electric.sector <- Electric.sector.intermittent.technology <-
intermittent.technology <- subsector_1 <- sector <- fuel <- Electric.sector.technology <-
water_sector <- water_type <- state <- state_name <- ':=' <- x <- plant_type <- State <-
value <- Basin_name <- Electric.sector <- Electric.sector.technology <-
apply.to <- GCAM_basin_ID <- basin_name <- calOutputValue <- capital.overnight <-
cooling_system <- deflator <- efficiency <- fixed.charge.rate <- from.subsector <-
from.supplysector <- from.technology <- from.year <- global.share.weight <-
input.capital <- input.cost <- input.unit <- intensity_CORE <-
intermittent.technology <- interpolation.function <- loadfactor_CORE <-
logit.exponent <- logit.type <- logit.year.fillout <- median.shutdown.point <-
non_fuel_cost_core <- out_MWh.sea <- out_MWh_sea <- output.unit <-
passthrough.sector <- plant_type <- price.unit <- region <- sce <- sector.name <- share <-
share.weight <- share.weight.sum <- share.weight.year <- share_nat.sea <- state <-
state.cooling.share.weight <- state.to.country.share <- state_abbr <-
stub.technology <- subs.share.weight <- subsector <- subsector.1 <-
subsector.name <- subsector.name0 <- subsector0 <- subsector_1 <- supplysector <-
supplysector.1 <- tag <- tech.share.weight <- technology <- technology.x <-
technology.y <- to.subsector <- to.supplysector <- to.technology <- to.value <-
to.year <- updated.share.weight <- value <- volume <- water_sector <- water_type <-
weight_EJ_core <- wt_short <- year <- GLU_name <- future.subs.shrwt <- hist.share <- NULL
# ===================================================
# 1. Read files
# Load required inputs
A23.elecS_tech_mapping_cool <- get_data(all_data, "gcam-usa/A23.elecS_tech_mapping_cool", strip_attributes = TRUE)
elec_tech_water_map <- get_data(all_data, "gcam-usa/elec_tech_water_map", strip_attributes = TRUE)
A23.elecS_tech_mapping_cool_shares_fut <- get_data(all_data, "gcam-usa/A23.elecS_tech_mapping_cool_shares_fut", strip_attributes = TRUE)
usa_seawater_states_basins <- get_data(all_data, "gcam-usa/usa_seawater_states_basins", strip_attributes = TRUE)
L1233.out_EJ_state_elec_F_tech_cool <- get_data(all_data, "L1233.out_EJ_state_elec_F_tech_cool", strip_attributes = TRUE)
L2233.GlobalTechEff_elec_cool <- get_data(all_data, "L2233.GlobalTechEff_elec_cool", strip_attributes = TRUE)
L2233.GlobalTechShrwt_elec_cool <- get_data(all_data, "L2233.GlobalTechShrwt_elec_cool", strip_attributes = TRUE)
L2233.GlobalTechProfitShutdown_elec_cool <- get_data(all_data, "L2233.GlobalTechProfitShutdown_elec_cool", strip_attributes = TRUE)
L2233.GlobalTechCapital_elec_cool <- get_data(all_data, "L2233.GlobalTechCapital_elec_cool", strip_attributes = TRUE)
L2233.GlobalTechCapital_elecPassthru <- get_data(all_data, "L2233.GlobalTechCapital_elecPassthru", strip_attributes = TRUE)
L2233.GlobalTechCoef_elec_cool <- get_data(all_data, "L2233.GlobalTechCoef_elec_cool", strip_attributes = TRUE)
L2233.GlobalIntTechCapital_elec_cool <- get_data(all_data, "L2233.GlobalIntTechCapital_elec_cool", strip_attributes = TRUE)
L2233.GlobalIntTechEff_elec_cool <- get_data(all_data, "L2233.GlobalIntTechEff_elec_cool", strip_attributes = TRUE)
L2233.GlobalIntTechCoef_elec_cool <- get_data(all_data, "L2233.GlobalIntTechCoef_elec_cool", strip_attributes = TRUE)
L2234.AvgFossilEffKeyword_elecS_USA <- get_data(all_data, "L2234.AvgFossilEffKeyword_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechBackup_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechBackup_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechCapital_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechCapital_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechEff_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechEff_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechLifetime_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechLifetime_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechOMfixed_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechOMfixed_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechOMvar_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechOMvar_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechShrwt_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechShrwt_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechCapFac_elecS_USA <- get_data(all_data,"L2234.GlobalTechCapFac_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechCapital_elecS_USA <- get_data(all_data,"L2234.GlobalTechCapital_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechCapture_elecS_USA <- get_data(all_data,"L2234.GlobalTechCapture_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechEff_elecS_USA <- get_data(all_data,"L2234.GlobalTechEff_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechLifetime_elecS_USA <- get_data(all_data,"L2234.GlobalTechLifetime_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechOMfixed_elecS_USA <- get_data(all_data,"L2234.GlobalTechOMfixed_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechOMvar_elecS_USA <- get_data(all_data,"L2234.GlobalTechOMvar_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechProfitShutdown_elecS_USA <- get_data(all_data,"L2234.GlobalTechProfitShutdown_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechSCurve_elecS_USA <- get_data(all_data,"L2234.GlobalTechSCurve_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechShrwt_elecS_USA <- get_data(all_data,"L2234.GlobalTechShrwt_elecS_USA", strip_attributes = TRUE)
L2234.PrimaryRenewKeyword_elecS_USA <- get_data(all_data,"L2234.PrimaryRenewKeyword_elecS_USA", strip_attributes = TRUE)
L2234.PrimaryRenewKeywordInt_elecS_USA <- get_data(all_data,"L2234.PrimaryRenewKeywordInt_elecS_USA", strip_attributes = TRUE)
L2234.StubTechCapFactor_elecS_solar_USA <- get_data(all_data,"L2234.StubTechCapFactor_elecS_solar_USA", strip_attributes = TRUE)
L2234.StubTechCapFactor_elecS_wind_USA <- get_data(all_data,"L2234.StubTechCapFactor_elecS_wind_USA", strip_attributes = TRUE)
L2234.StubTechEff_elecS_USA <- get_data(all_data,"L2234.StubTechEff_elecS_USA", strip_attributes = TRUE)
L2234.StubTechElecMarket_backup_elecS_USA <- get_data(all_data,"L2234.StubTechElecMarket_backup_elecS_USA", strip_attributes = TRUE)
L2234.StubTechFixOut_elecS_USA <- get_data(all_data,"L2234.StubTechFixOut_elecS_USA", strip_attributes = TRUE)
L2234.StubTechFixOut_hydro_elecS_USA <- get_data(all_data,"L2234.StubTechFixOut_hydro_elecS_USA", strip_attributes = TRUE)
L2234.StubTechMarket_backup_elecS_USA <- get_data(all_data,"L2234.StubTechMarket_backup_elecS_USA", strip_attributes = TRUE)
L2234.StubTechMarket_elecS_USA <- get_data(all_data,"L2234.StubTechMarket_elecS_USA", strip_attributes = TRUE)
L2234.StubTechProd_elecS_USA <- get_data(all_data,"L2234.StubTechProd_elecS_USA", strip_attributes = TRUE)
L2234.SubsectorLogit_elecS_USA <- get_data(all_data,"L2234.SubsectorLogit_elecS_USA", strip_attributes = TRUE)
L2234.SubsectorShrwt_elecS_USA <- get_data(all_data,"L2234.SubsectorShrwt_elecS_USA", strip_attributes = TRUE)
L2234.SubsectorShrwtInterp_elecS_USA <- get_data(all_data,"L2234.SubsectorShrwtInterp_elecS_USA", strip_attributes = TRUE)
L2234.SubsectorShrwtInterpTo_elecS_USA <- get_data(all_data,"L2234.SubsectorShrwtInterpTo_elecS_USA", strip_attributes = TRUE)
L2234.Supplysector_elecS_USA <- get_data(all_data,"L2234.Supplysector_elecS_USA", strip_attributes = TRUE)
L2234.StubTechCost_offshore_wind_elecS_USA <- get_data(all_data,"L2234.StubTechCost_offshore_wind_elecS_USA", strip_attributes = TRUE)
L2241.GlobalTechCapFac_elec_coalret_USA <- get_data(all_data, "L2241.GlobalTechCapFac_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechCapital_elec_coalret_USA <- get_data(all_data,"L2241.GlobalTechCapital_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechEff_elec_coalret_USA <- get_data(all_data,"L2241.GlobalTechEff_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechOMfixed_elec_coalret_USA <- get_data(all_data,"L2241.GlobalTechOMfixed_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechOMvar_elec_coalret_USA <- get_data(all_data,"L2241.GlobalTechOMvar_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechProfitShutdown_elec_coalret_USA <- get_data(all_data,"L2241.GlobalTechProfitShutdown_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechShrwt_elec_coalret_USA <- get_data(all_data,"L2241.GlobalTechShrwt_elec_coalret_USA", strip_attributes = TRUE)
L2241.StubTechEff_elec_coalret_USA <- get_data(all_data,"L2241.StubTechEff_elec_coalret_USA", strip_attributes = TRUE)
L2241.StubTechMarket_elec_coalret_USA <- get_data(all_data,"L2241.StubTechMarket_elec_coalret_USA", strip_attributes = TRUE)
L2241.StubTechProd_elec_coalret_USA <- get_data(all_data,"L2241.StubTechProd_elec_coalret_USA", strip_attributes = TRUE)
L2241.StubTechSCurve_elec_coalret_USA <- get_data(all_data,"L2241.StubTechSCurve_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechCapFac_coal_vintage_USA <- get_data(all_data,"L2241.GlobalTechCapFac_coal_vintage_USA", strip_attributes = TRUE)
L2241.GlobalTechCapital_coal_vintage_USA <- get_data(all_data,"L2241.GlobalTechCapital_coal_vintage_USA", strip_attributes = TRUE)
L2241.GlobalTechEff_coal_vintage_USA <- get_data(all_data,"L2241.GlobalTechEff_coal_vintage_USA", strip_attributes = TRUE)
L2241.GlobalTechOMfixed_coal_vintage_USA <- get_data(all_data,"L2241.GlobalTechOMfixed_coal_vintage_USA", strip_attributes = TRUE)
L2241.GlobalTechOMvar_coal_vintage_USA <- get_data(all_data,"L2241.GlobalTechOMvar_coal_vintage_USA", strip_attributes = TRUE)
L2241.GlobalTechShrwt_coal_vintage_USA <- get_data(all_data,"L2241.GlobalTechShrwt_coal_vintage_USA", strip_attributes = TRUE)
L2241.StubTechEff_coal_vintage_USA <- get_data(all_data,"L2241.StubTechEff_coal_vintage_USA", strip_attributes = TRUE)
L2241.StubTechMarket_coal_vintage_USA <- get_data(all_data,"L2241.StubTechMarket_coal_vintage_USA", strip_attributes = TRUE)
L2241.StubTechProd_coal_vintage_USA <- get_data(all_data,"L2241.StubTechProd_coal_vintage_USA", strip_attributes = TRUE)
L2241.StubTechProfitShutdown_coal_vintage_USA <- get_data(all_data,"L2241.StubTechProfitShutdown_coal_vintage_USA", strip_attributes = TRUE)
L2241.StubTechSCurve_coal_vintage_USA <- get_data(all_data,"L2241.StubTechSCurve_coal_vintage_USA", strip_attributes = TRUE)
# ===================================================
# Define unique states and basins that have access to seawater that will
# allow for seawate cooling
seawater_states_basins <- unique(usa_seawater_states_basins$seawater_region)
# Process data
A23.elecS_tech_mapping_cool %>%
select(-supplysector, -water_type, -cooling_system, -plant_type) ->
A23.elecS_tech_mapping_cool
## Define several filtering and renaming fuctions that will be applied
## throughout the zchunk
# To account for new nesting-subsector structure and to add cooling technologies,
# we must expand certain outputs
add_cooling_techs <- function(data){
data %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("stub.technology" = "Electric.sector.technology",
"supplysector" = "Electric.sector","subsector")) %>%
select(-technology, -subsector_1)%>%
rename(technology = to.technology,
subsector0 = subsector,
subsector = stub.technology) -> data_new
data_new %>%
filter(grepl(gcamusa.WATER_TYPE_SEAWATER,technology),
(region %in% seawater_states_basins)) %>%
bind_rows(data_new %>%
filter(!grepl(gcamusa.WATER_TYPE_SEAWATER,technology))) %>%
arrange(region,year) -> data_new
return(data_new)
}
add_global_cooling_techs <- function(data){
data %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("technology" = "Electric.sector.technology",
"supplysector" = "Electric.sector",
"subsector")) %>%
select(-subsector_1, -technology.y) %>%
rename(sector.name = supplysector,
subsector.name0 = subsector,
subsector.name = technology,
technology = to.technology) %>%
mutate(technology = if_else(subsector.name0 == "wind" | subsector.name0 == "solar", subsector.name,
if_else(subsector.name0 == "grid_storage", subsector.name0, technology))) ->
data_new
return(data_new)
}
add_int_cooling_techs <- function(data){
data %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("supplysector" = "Electric.sector",
"intermittent.technology" = "Electric.sector.technology",
"subsector")) %>%
select(-technology, -subsector_1)%>%
rename(subsector0 = subsector,
subsector = intermittent.technology,
intermittent.technology = to.technology) ->
data_new
return(data_new)
}
# Here we will consolidate coal retire + coal vintages + other electricity subsectors that are
# currently located in separate files
# This also adds each cooling technology and trasfers coefficients calculated for cooling techs if needed
# All variables here are global
L2234.GlobalTechEff_elecS_USA %>%
bind_rows((L2241.GlobalTechEff_coal_vintage_USA %>%
rename(supplysector = sector.name,
subsector = subsector.name)),
L2241.GlobalTechEff_elec_coalret_USA) %>%
add_global_cooling_techs() %>%
select(-efficiency) %>%
# Bring in global cooling tech efficiencies from GCAM-core
left_join_keep_first_only(L2233.GlobalTechEff_elec_cool %>%
mutate(technology = gsub("_storage.*", "_base_storage", technology)) %>%
select(technology, efficiency,year),
by = c("technology", "year")) %>%
arrange(sector.name,year)->
L2233.GlobalTechEff_elec_cool_USA
L2234.GlobalTechShrwt_elecS_USA %>%
bind_rows(L2241.GlobalTechShrwt_coal_vintage_USA,
L2241.GlobalTechShrwt_elec_coalret_USA) %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("technology" = "Electric.sector.technology",
"sector.name" = "Electric.sector",
"subsector.name" = "subsector")) %>%
select(-subsector_1, -technology.y) %>%
rename(subsector.name0 = subsector.name, subsector.name = technology, technology = to.technology) %>%
mutate(technology = if_else(subsector.name0 == "wind" | subsector.name0 == "solar", subsector.name,
if_else(subsector.name0 == "grid_storage", subsector.name0, technology))) %>%
arrange(sector.name,year) ->
L2233.GlobalTechShrwt_elec_cool_USA
# Add all vintages to profit shutdown tibbles as they initially exist at state level, not global
L2234.GlobalTechProfitShutdown_elecS_USA %>%
bind_rows(L2241.GlobalTechProfitShutdown_elec_coalret_USA) %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("technology" = "Electric.sector.technology",
"supplysector" = "Electric.sector",
"subsector")) %>%
select(-subsector_1, -median.shutdown.point, -technology.y) %>%
rename(subsector0 = subsector, subsector = technology, technology = to.technology)%>%
left_join_keep_first_only(L2233.GlobalTechProfitShutdown_elec_cool %>%
## Keep_first_only is used to avoid unnessary
## multiplication of rows. We only want to bring
## in the global profit shutdowns for the technologies
## defined
select(technology, median.shutdown.point),
by=c("technology")) %>%
arrange(supplysector, year) %>%
mutate(technology = if_else(subsector0 == "wind" | subsector0 == "solar", subsector,
if_else(subsector0 == "grid_storage", subsector0, technology))) ->
L2233.GlobalTechProfitShutdown_elec_cool_USA
L2234.GlobalTechOMvar_elecS_USA %>%
bind_rows(L2241.GlobalTechOMvar_coal_vintage_USA %>%
rename(supplysector = sector.name,
subsector = subsector.name),
L2241.GlobalTechOMvar_elec_coalret_USA) %>%
add_global_cooling_techs() %>%
arrange(sector.name, year) ->
L2233.GlobalTechOMvar_elec_USA
L2234.GlobalTechOMfixed_elecS_USA %>%
bind_rows(L2241.GlobalTechOMfixed_coal_vintage_USA %>%
rename(supplysector = sector.name,
subsector = subsector.name),
L2241.GlobalTechOMfixed_elec_coalret_USA) %>%
add_global_cooling_techs() %>%
arrange(sector.name, year) ->
L2233.GlobalTechOMfixed_elec_USA
L2234.GlobalTechCapital_elecS_USA %>%
bind_rows(L2241.GlobalTechCapital_coal_vintage_USA %>%
rename(supplysector = sector.name,
subsector = subsector.name),
L2241.GlobalTechCapital_elec_coalret_USA) %>%
add_global_cooling_techs() %>%
arrange(sector.name, year) ->
L2233.GlobalTechCapital_elec_USA
L2233.GlobalTechCapital_elec_USA %>%
select(-input.capital, -capital.overnight, -fixed.charge.rate) %>%
left_join_keep_first_only(
## keep first only allows for capital costs to be pulled in the GCAM-core
## without unnecessary duplication caused by LJ. LJENM throws error.
bind_rows(L2233.GlobalTechCapital_elec_cool %>%
mutate(technology = gsub("storage", "base_storage", technology)),
L2233.GlobalTechCapital_elecPassthru %>%
mutate(technology=gsub("storage", "base_storage", technology))) %>%
select(technology, input.capital, capital.overnight, fixed.charge.rate),
by = c("technology")) %>%
arrange(sector.name,year) %>%
mutate(technology = if_else(subsector.name0 == "wind" | subsector.name0 == "solar", subsector.name,
if_else(subsector.name0 == "grid_storage", subsector.name0, technology))) %>%
na.omit()->
# remove battery options as they have no cooling options
L2233.GlobalTechCapital_elec_cool_USA
L2234.GlobalTechCapFac_elecS_USA %>%
bind_rows(L2241.GlobalTechCapFac_coal_vintage_USA %>%
rename(supplysector = sector.name,
subsector = subsector.name),
L2241.GlobalTechCapFac_elec_coalret_USA) %>%
add_global_cooling_techs() %>%
arrange(sector.name, year) ->
L2233.GlobalTechCapFac_elec_USA
# If there are not s-curves, specifically for coal, defined at the state level (L2233.StubTechSCurve_elec_USA below), we will
# we will assume that they follow the predefined lifetime and s-curves for all other techs
L2234.GlobalTechSCurve_elecS_USA %>%
add_global_cooling_techs() %>%
rename(supplysector = sector.name) %>%
arrange(supplysector, year) ->
L2233.GlobalTechSCurve_elecS_USA
# Assume that global tech coefficients map to all segments
L2233.GlobalTechCoef_elec_cool %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("subsector.name" = "technology",
"technology" = "to.technology")) %>%
select(-sector.name, -subsector_1, -subsector.name) %>%
na.omit() %>%
bind_rows(
L2233.GlobalTechCoef_elec_cool %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("subsector.name" = "technology")) %>%
filter(grepl("base_storage", to.technology)) %>%
select(-sector.name, -subsector_1, -subsector.name, -technology) %>%
rename(technology = to.technology) %>%
na.omit(),
L2233.GlobalTechCoef_elec_cool %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("technology")) %>%
filter(grepl("hydro", to.technology) | grepl("PV_base_storage", to.technology)) %>%
select(-sector.name, -subsector_1, -subsector.name, -technology) %>%
rename(technology = to.technology)) %>%
rename(supplysector = Electric.sector,
subsector0 = subsector,
subsector = Electric.sector.technology) %>%
right_join(L2233.GlobalTechEff_elec_cool_USA %>%
# Add all fuel, power plant, cooling tech, and all years
select(sector.name,subsector.name0,subsector.name,technology),
by = c("supplysector" = "sector.name",
"subsector0" = "subsector.name0",
"subsector" = "subsector.name",
"technology")) %>%
arrange(supplysector, subsector0, subsector, technology, year) %>%
na.omit() %>%
unique() ->
L2233.GlobalTechCoef_elecS_cool_USA
L2234.GlobalTechCapture_elecS_USA %>%
add_global_cooling_techs() %>%
rename(supplysector = sector.name) %>%
arrange(supplysector, year) ->
L2233.GlobalTechCapture_elecS_USA
# Coal vintage lifetimes are added at state level, therefore we remove all coal conv pul from the Global Lifetime values
L2234.GlobalTechLifetime_elecS_USA %>%
add_global_cooling_techs() %>%
rename(supplysector = sector.name) %>%
arrange(supplysector, year) ->
L2233.GlobalTechLifetime_elecS_cool_USA
L2234.AvgFossilEffKeyword_elecS_USA %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("technology" = "Electric.sector.technology",
"sector.name" = "Electric.sector",
"subsector.name" = "subsector")) %>%
select(-subsector_1, -technology.y) %>%
rename(subsector = technology,
technology = to.technology,
subsector.name0 = subsector.name) %>%
arrange(sector.name,year) ->
L2233.AvgFossilEffKeyword_elecS_USA
# Introduce GlobalInt techs
# We filter out all non-csp techs initially as these are these are the techs
# are the ones which need cooling techs added
csp_filter <- function(data){
data %>%
filter(!grepl("CSP", intermittent.technology)) %>%
rename(subsector0 = subsector,
subsector = intermittent.technology) %>%
mutate(intermittent.technology = subsector) ->
data_new
return(data_new)
}
# no changes needed for backup techs as cooling is not directly associated in previous cooling files
L2234.GlobalIntTechBackup_elecS_USA %>%
csp_filter() %>%
bind_rows(L2234.GlobalIntTechBackup_elecS_USA %>%
filter(grepl("CSP", intermittent.technology)) %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("supplysector" = "Electric.sector",
"intermittent.technology" = "Electric.sector.technology",
"subsector")) %>%
select(-technology, -subsector_1) %>%
rename(subsector0 = subsector,
subsector = intermittent.technology,
intermittent.technology = to.technology)) %>%
arrange(supplysector, subsector0, subsector, intermittent.technology, year)->
L2233.GlobalIntTechBackup_elecS_USA
# isolate int techs that do not have cooling techs associated
L2234.GlobalIntTechCapital_elecS_USA %>%
csp_filter() ->
L2233.GlobalIntTechCapital_elecS_USA
# Isolate CSP techs that have two capital costs
L2234.GlobalIntTechCapital_elecS_USA %>%
filter(grepl("CSP", intermittent.technology)) %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("intermittent.technology" = "Electric.sector.technology",
"supplysector" = "Electric.sector", "subsector")) %>%
select(-technology, -subsector_1) %>%
rename(subsector0 = subsector,
subsector = intermittent.technology,
intermittent.technology = to.technology) ->
L2233.GlobalIntTechCapital_elecS_cool_USA
L2233.GlobalIntTechCapital_elec_cool %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("subsector.name" = "subsector_1")) %>%
select(-sector.name, -subsector.name, -technology.x, -technology.y) %>%
rename(supplysector = Electric.sector,
subsector0 = subsector,
subsector = Electric.sector.technology,
intermittent.technology = to.technology) %>%
bind_rows(L2233.GlobalIntTechCapital_elecS_USA,
L2233.GlobalIntTechCapital_elecS_cool_USA) %>%
filter(!grepl("CSP_base", subsector)) %>%
# There are no additional cases of CSP_base across other Int Techs, therefore, we will remove
# as this has been introduced by calling gcam-core file L2233.GlobalIntTechCapital_elec_cool
arrange(supplysector, subsector0, subsector, intermittent.technology, year)->
L2233.GlobalIntTechCapital_elecS_cool_USA
# isolate CSP sectors which will need cooling tech layer added
L2234.GlobalIntTechEff_elecS_USA %>%
csp_filter()->
L2233.GlobalIntTechEff_elecS_USA
L2233.GlobalIntTechEff_elec_cool %>%
filter(grepl("CSP", technology)) %>%
mutate(technology = gsub("CSP", "CSP_storage", technology)) %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("subsector.name" = "subsector_1")) %>%
select(-sector.name, -subsector.name, -technology.y, -technology.x) %>%
filter((grepl("dry_hybrid", to.technology) & efficiency < 0.96)) %>%
# As we are not matching CSP names directly here, we want to make sure that the efficiency
# designated to dry_hybrid, 0.95, is the one that is adopted for all CSP (dry_hybrid) segments
bind_rows(L2233.GlobalIntTechEff_elec_cool %>%
filter(grepl("CSP", technology)) %>%
mutate(technology = gsub("CSP", "CSP_storage", technology)) %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("subsector.name" = "subsector_1")) %>%
select(-sector.name, -subsector.name, -technology.y, -technology.x) %>%
# As we are not matching CSP names directly here, we want to make sure that the efficiency
# designated to dry_hybrid, 0.95, is the one that is adopted for all CSP (dry_hybrid) segments
filter((grepl("recirculating", to.technology) & efficiency > 0.96))) %>%
rename(supplysector = Electric.sector,
subsector0 = subsector,
subsector = Electric.sector.technology,
intermittent.technology = to.technology) %>%
bind_rows(L2233.GlobalIntTechEff_elecS_USA) %>%
filter(subsector != "CSP_base") %>%
# There are no additional cases of CSP_base across other Int Techs, therefore, we will remove
# as this has been introduced by calling gcam-core file L2233.GlobalIntTechEff_elec_cool
arrange(supplysector, subsector0, subsector, intermittent.technology, year) ->
L2233.GlobalIntTechEff_elecS_cool_USA
# Add global water coefs from gcam-core to GCAM-USA. Maintain the global coefs
# Recommended to create state level water demand coefs in the future as state-level coefs are not currently applied
L2233.GlobalIntTechCoef_elec_cool %>%
# GCAM-core data has the subsector names for PV = solar, yet CSP = CSP, so we change the subsector
# name to allow for the mapping to be applied to PV as well
mutate(subsector.name = if_else(grepl("solar", subsector.name), technology, subsector.name)) %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("subsector.name" = "subsector_1")) %>%
select(-sector.name, -subsector.name, -technology.y, -technology.x) %>%
rename(supplysector = Electric.sector,
subsector0 = subsector,
subsector = Electric.sector.technology,
intermittent.technology = to.technology) %>%
filter(!grepl("base_storage", subsector)) %>%
# PV and CSP base storage are not intermittent techs, therefore, we will remove
# as these have been introduced by calling gcam-core file L2233.GlobalIntTechEff_elec_cool
arrange(supplysector, subsector0, subsector, intermittent.technology, year) ->
L2233.GlobalIntTechCoef_elecS_cool_USA
L2234.GlobalIntTechLifetime_elecS_USA %>%
csp_filter() %>%
bind_rows(L2234.GlobalIntTechLifetime_elecS_USA %>%
filter(grepl("CSP", intermittent.technology)) %>%
add_int_cooling_techs) %>%
arrange(supplysector, subsector0, subsector, intermittent.technology, year) ->
L2233.GlobalIntTechLifetime_elecS_cool_USA
L2234.GlobalIntTechOMfixed_elecS_USA %>%
csp_filter() %>%
bind_rows(L2234.GlobalIntTechOMfixed_elecS_USA %>%
filter(grepl("CSP", intermittent.technology)) %>%
add_int_cooling_techs) %>%
arrange(supplysector, subsector0, subsector, intermittent.technology, year) ->
L2233.GlobalIntTechOMfixed_elecS_cool_USA
L2234.GlobalIntTechOMvar_elecS_USA %>%
mutate(subsector0 = subsector,
subsector = intermittent.technology) ->
L2233.GlobalIntTechOMvar_elecS_cool_USA
L2234.GlobalIntTechOMvar_elecS_USA %>%
mutate(subsector0 = subsector,
subsector = intermittent.technology) ->
L2233.GlobalIntTechOMvar_elecS_cool_USA
L2234.GlobalIntTechShrwt_elecS_USA %>%
filter(!grepl("CSP", intermittent.technology)) %>%
rename(subsector.name0 = subsector.name,
subsector.name = intermittent.technology) %>%
mutate(intermittent.technology = subsector.name) %>%
bind_rows(L2234.GlobalIntTechShrwt_elecS_USA %>%
filter(grepl("CSP", intermittent.technology)) %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("sector.name" = "Electric.sector",
"intermittent.technology" = "Electric.sector.technology",
"subsector.name" = "subsector")) %>%
select(-technology, -subsector_1) %>%
rename(subsector.name0 = subsector.name,
subsector.name = intermittent.technology,
intermittent.technology = to.technology)) %>%
arrange(sector.name, subsector.name0, subsector.name, intermittent.technology, year) ->
L2233.GlobalIntTechShrwt_elecS_cool_USA
L2234.PrimaryRenewKeyword_elecS_USA %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by=c("technology" = "Electric.sector.technology",
"sector.name" = "Electric.sector",
"subsector.name" = "subsector")) %>%
select(-subsector_1, -technology.y) %>%
rename(subsector = technology,
technology = to.technology,
subsector.name0 = subsector.name) %>%
arrange(sector.name, year) ->
L2233.PrimaryRenewKeyword_elecS_cool_USA
L2234.PrimaryRenewKeywordInt_elecS_USA %>%
filter(!grepl("CSP", intermittent.technology)) %>%
rename(subsector.name0 = subsector.name,
subsector.name = intermittent.technology) %>%
mutate(intermittent.technology = subsector.name) %>%
bind_rows(L2234.PrimaryRenewKeywordInt_elecS_USA %>%
filter(grepl("CSP", intermittent.technology)) %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("sector.name" = "Electric.sector",
"intermittent.technology" = "Electric.sector.technology",
"subsector.name" = "subsector")) %>%
select(-technology, -subsector_1) %>%
rename(subsector.name0 = subsector.name,
subsector.name = intermittent.technology,
intermittent.technology = to.technology)) %>%
arrange(sector.name, subsector.name0, subsector.name, intermittent.technology, year) ->
L2233.PrimaryRenewKeywordInt_elecS_cool_USA
# We can now look to state level data, once again combining vintages and adding cooling technologies
# Efficiencies do not change with the addition of cooling techs
L2234.StubTechEff_elecS_USA %>%
bind_rows(L2241.StubTechEff_coal_vintage_USA,
L2241.StubTechEff_elec_coalret_USA) %>%
add_cooling_techs() %>%
mutate(technology = if_else(subsector0 == "grid_storage", subsector0, technology)) ->
L2233.StubTechEff_elec_USA
L2234.StubTechMarket_elecS_USA %>%
bind_rows(L2241.StubTechMarket_coal_vintage_USA,
L2241.StubTechMarket_elec_coalret_USA) %>%
add_cooling_techs() %>%
mutate(technology = if_else(grepl("base_storage", subsector0), subsector0,
if_else(grepl("wind_base", subsector), subsector, technology))) ->
# temporary placement of base_storage cooling techs = nesting subsector
L2233.StubTechMarket_elec_USA
L1233.out_EJ_state_elec_F_tech_cool %>%
filter(year %in% MODEL_BASE_YEARS) %>%
left_join_error_no_match(elec_tech_water_map %>%
select(-from.supplysector, -from.subsector, -from.technology,
-minicam.energy.input, -sector, -to.subsector,-to.supplysector),
by = c("fuel", "technology", "cooling_system", "water_type")) %>%
select(-plant_type, -technology, -cooling_system, -water_type) %>%
rename(supplysector = sector, subsector0 = fuel, technology = to.technology, region = state) %>%
ungroup() ->
L1233.out_EJ_state_elec_F_tech_cool
# Combine elec segments, coal retire, and coal vintage calibrated production tables
L2234.StubTechProd_elecS_USA %>%
rename(tech.share.weight=share.weight) %>%
# use anti join to filter out entries in elec segments table which will be
# overwritten by coal retire technologies
anti_join(L2241.StubTechProd_elec_coalret_USA,
by = c("region", "supplysector", "subsector", "stub.technology", "year")) %>%
bind_rows(L2241.StubTechProd_elec_coalret_USA) %>%
# use anti join to filter out entries in table which will be overwritten
# by coal vintage technologies
anti_join(L2241.StubTechProd_coal_vintage_USA,
by = c("region", "supplysector", "subsector", "stub.technology", "year")) %>%
bind_rows(L2241.StubTechProd_coal_vintage_USA) %>%
add_cooling_techs() ->
L2233.StubTechProd_elec_USA
L2233.StubTechProd_elec_USA %>%
filter(calOutputValue > 0) %>%
left_join_keep_first_only(L1233.out_EJ_state_elec_F_tech_cool,
by = c("supplysector", "subsector0", "subsector", "technology", "region", "share.weight.year" = "year")) %>%
replace_na(list(share = 0)) %>%
group_by(supplysector, subsector0, subsector, region, year) %>%
# Divide by 2 to account for recirculating and dry_cooling technology types in CSP.
# These cooling shares are not included in L1233.out_EJ_state_elec_F_tech_cool.
mutate(calOutputValue = if_else(grepl("CSP", subsector), calOutputValue / 2,
# wind & pv don't have cooling techs and are assigned zero shares based on the replace_na above
# assign full calOutput value
if_else(subsector0 == "wind" | grepl("PV", subsector), calOutputValue, calOutputValue * share))) %>%
replace_na(list(calOutputValue = 0)) %>%
select(-value, -share) %>%
ungroup() %>%
unique() %>%
bind_rows(L2233.StubTechProd_elec_USA %>%
filter(calOutputValue == 0)) %>%
mutate(tech.share.weight = if_else(calOutputValue > 0, 1, 0)) %>%
group_by(supplysector, subsector0, subsector, region, year) %>%
mutate(subs.share.weight = if_else(sum(calOutputValue) > 0, 1, 0)) %>%
ungroup() %>%
arrange(region, supplysector, subsector0, year) ->
L2233.StubTechProd_elec_USA
# State level s-curves, combining vintages and initial slow and fast retire plants
bind_rows(L2241.StubTechSCurve_coal_vintage_USA,
L2241.StubTechSCurve_elec_coalret_USA) %>%
add_cooling_techs() ->
L2233.StubTechSCurve_elec_USA
L2241.StubTechProfitShutdown_coal_vintage_USA %>%
add_cooling_techs() ->
L2233.StubTechProfitShutdown_elecS_cool_USA
L2234.StubTechCapFactor_elecS_solar_USA %>%
add_cooling_techs() ->
L2233.StubTechCapFactor_elecS_solar_USA
L2234.StubTechCapFactor_elecS_wind_USA %>%
add_cooling_techs() %>%
mutate(technology = if_else(grepl("wind_base", subsector), subsector, technology)) ->
L2233.StubTechCapFactor_elecS_wind_USA
L2234.StubTechElecMarket_backup_elecS_USA %>%
add_cooling_techs() %>%
mutate(technology = if_else(subsector == "rooftop_pv" | grepl("wind_base", subsector), subsector, technology)) ->
L2233.StubTechElecMarket_backup_elecS_USA
L2234.StubTechFixOut_elecS_USA %>%
add_cooling_techs() ->
L2233.StubTechFixOut_elecS_USA
L2234.StubTechFixOut_hydro_elecS_USA %>%
add_cooling_techs() ->
L2233.StubTechFixOut_hydro_elecS_USA
L2234.StubTechMarket_backup_elecS_USA %>%
add_cooling_techs() %>%
mutate(technology = if_else(subsector == "rooftop_pv" | grepl("wind_base", subsector), subsector, technology)) ->
L2233.StubTechMarket_backup_elecS_USA
L2234.StubTechCost_offshore_wind_elecS_USA %>%
add_cooling_techs() ->
L2233.StubTechCost_offshore_wind_elecS_USA
L2234.SubsectorLogit_elecS_USA %>%
rename(subsector0 = subsector) %>%
mutate(subsector.1 = subsector0) %>%
select(-subsector.1) %>%
arrange(supplysector) ->
L2233.SubsectorLogit_elecS_USA
# Create logit table at subsector level by including all possible fule types (i.e. hydro, battery, etc.)
L2234.SubsectorLogit_elecS_USA %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("supplysector" = "Electric.sector", "subsector")) %>%
rename(subsector0 = subsector,
subsector = Electric.sector.technology) %>%
right_join(bind_rows(L2233.StubTechMarket_elec_USA %>%
select(subsector, region, technology),
L2233.StubTechFixOut_hydro_elecS_USA %>%
select(subsector, region, technology),
L2233.StubTechEff_elec_USA %>%
filter(subsector == "battery") %>%
select(subsector, region, technology)),
# Including all possible technologies here
by = c("subsector", "region", "to.technology" = "technology")) %>%
select(region, supplysector, subsector0, subsector, logit.year.fillout, logit.exponent,logit.type) %>%
# Acknowledge that not all vintages are in each state, therefore shareweights and logits are
# not needed for these vintages
unique() %>%
arrange(supplysector) ->
L2233.SubsectorLogit_elecS_cool_USA
L2233.SubsectorLogit_elecS_cool_USA %>%
select(region, supplysector, subsector0, subsector) %>%
# select which load segment fuel + power plant exist in each state
left_join(L2233.GlobalTechCoef_elecS_cool_USA,
## LJ used as coefficients are added for all historical years for only the
## load segement, fuel, and power plants that exist. This increases data set size,
## requiring LJ.
by = c("supplysector", "subsector0", "subsector")) %>%
mutate(market.name = if_else(minicam.energy.input == gcamusa.WATER_TYPE_SEAWATER, gcam.USA_REGION, region)) %>%
na.omit() ->
L2233.StubTechCoef_elecS_cool_USA
L2233.StubTechCoef_elecS_cool_USA %>%
filter(grepl(gcamusa.WATER_TYPE_SEAWATER, technology),
(region %in% seawater_states_basins)) %>%
bind_rows(L2233.StubTechCoef_elecS_cool_USA %>%
filter(!grepl(gcamusa.WATER_TYPE_SEAWATER, technology))) %>%
arrange(region, year) ->
# Not all techs have cooling options, therefore we remove these
L2233.StubTechCoef_elecS_cool_USA
L2234.SubsectorShrwt_elecS_USA %>%
rename(subsector0 = subsector) %>%
bind_rows(
L2234.StubTechProd_elecS_USA %>%
select(region, supplysector, subsector, year, subs.share.weight) %>%
rename(share.weight = subs.share.weight, subsector0 = subsector) %>%
unique(),
L2234.StubTechFixOut_elecS_USA %>%
select(region, supplysector, subsector, year, subs.share.weight) %>%
rename(share.weight = subs.share.weight,
subsector0 = subsector) %>%
unique()
) %>%
arrange(region, supplysector, year) ->
L2233.SubsectorShrwt_elecS_USA
L2234.SubsectorShrwtInterp_elecS_USA %>%
rename(subsector0 = subsector) %>%
mutate(subsector.1 = subsector0) %>%
select(-subsector.1) %>%
arrange(supplysector) ->
L2233.SubsectorShrwtInterp_elecS_USA
L2234.SubsectorShrwtInterpTo_elecS_USA %>%
rename(subsector0 = subsector) %>%
mutate(subsector.1 = subsector0) %>%
select(-subsector.1) %>%
arrange(supplysector) ->
L2233.SubsectorShrwtInterpTo_elecS_USA
# Subsector shareweights are really generation technology shareweights
# These use the global tech object in L2234, so copy to all regions
# No interpolation function is needed
L2233.StubTechProd_elec_USA %>%
# calculate historical subsector (generation technology) shareweights
group_by(region, supplysector, subsector0, subsector, year) %>%
summarise(calOutputValue = sum(calOutputValue)) %>%
ungroup() %>%
# if no historical production, assign 0 shareweight; otherwise, assign 1 shareweight
mutate(share.weight = if_else(calOutputValue > 0, 1, 0)) %>%
select(-calOutputValue) ->
L2233.SubsectorShrwt_elecS_cool_USA_hist
L2234.GlobalTechShrwt_elecS_USA %>%
bind_rows(L2234.GlobalIntTechShrwt_elecS_USA %>%
rename(technology = intermittent.technology),
L2241.GlobalTechShrwt_elec_coalret_USA,
L2241.GlobalTechShrwt_coal_vintage_USA) %>%
repeat_add_columns(tibble::tibble(region = gcamusa.STATES)) %>%
rename(supplysector = sector.name,
subsector0 = subsector.name,
subsector = technology) %>%
# we only want future years here, because past years are dictated by state-level production
filter(year %in% MODEL_FUTURE_YEARS) %>%
# semi_join historical table to filter out techs that shouldn't be created,
# such as CSP and geothermal in regions without this resource
semi_join(L2233.SubsectorShrwt_elecS_cool_USA_hist,
by = c("region", "supplysector", "subsector0", "subsector")) %>%
select(region, supplysector, subsector0, subsector, year, share.weight) ->
L2233.SubsectorShrwt_elecS_cool_USA_fut
L2233.SubsectorShrwt_elecS_cool_USA_hist %>%
bind_rows(L2233.SubsectorShrwt_elecS_cool_USA_fut) %>%
arrange(region,supplysector,year) ->
L2233.SubsectorShrwt_elecS_cool_USA
# Prepare interpolation rules for all power plant + cooling system combinations
# First, we assume that if the generation technology exists in the historical period
# and is allowed to continue into future periods, the cooling technology shares will
# be held constant into the future. The exception is once through cooling, whose
# share weights will be 0 from 2020-2100 to mirror GCAM-core.
L2233.StubTechProd_elec_USA %>%
filter(year == max(MODEL_BASE_YEARS)) %>%
# join in subsector shareweights so we know which generation technologies
# are allowed to deploy in the future
left_join_error_no_match(L2233.SubsectorShrwt_elecS_cool_USA %>%
filter(year %in% (MODEL_FUTURE_YEARS)) %>%
group_by(region, supplysector, subsector0, subsector) %>%
# check if a generation tech has non-zero share-weight in any future period (i.e. sum > 0)
summarise(future.subs.shrwt = if_else(sum(share.weight) > 0, 1, 0)) %>%
ungroup(),
by = c("region", "supplysector", "subsector0", "subsector")) -> L2233.StubTechProd_elec_cool_SW_USA
# Set all once through technologies to zero in all future periods.
L2233.StubTechProd_elec_cool_SW_USA %>%
filter(grepl(gcamusa.DISALLOWED_COOLING_TECH, technology)) %>%
mutate(from.year = min(MODEL_FUTURE_YEARS),
to.year = max(MODEL_YEARS),
interpolation.function = gcamusa.FIXED_SHAREWEIGHT,
to.value = 0) %>%
rename(stub.technology = technology) %>%
mutate(apply.to = gcamusa.INTERP_APPLY_TO) %>%
select(region, supplysector, subsector0, subsector, stub.technology, apply.to,
from.year, to.year, to.value, interpolation.function) -> L2233.StubTechInterpTo_elecS_oncethrough_USA
# If the particular load segment / generation technology produced historically,
# fix technology (cooling system) share weights to calibration values
# for all future periods. We do this even if the particular load segment /
# generation technology is not allowed to deploy in the future - these assumptions
# are handled at the subsector (generation technology) level.
L2233.StubTechProd_elec_cool_SW_USA %>%
filter(!grepl(gcamusa.DISALLOWED_COOLING_TECH, technology),
subs.share.weight > 0 & future.subs.shrwt > 0) %>%
mutate(from.year = max(MODEL_BASE_YEARS),
to.year = max(MODEL_YEARS),
interpolation.function = gcamusa.FIXED_SHAREWEIGHT) %>%
rename(stub.technology = technology) %>%
mutate(apply.to = gcamusa.INTERP_APPLY_TO) %>%
select(region, supplysector, subsector0, subsector, stub.technology, apply.to,
from.year, to.year, interpolation.function) -> L2233.StubTechInterp_elecS_cool_USA
# Second, if a generation technology did not exist in the historical period (i.e. CSP, IGCC, etc.),
# but exists in the future, then the share weights for all non-once through cooling technologies
# will be set to 1.
# NOTE: In a very few instances, this includes generation technologies which produced historically
# but not in the given load segment in question. In these cases, we still set future share weights
# for all cooling techs to 1 in future periods, even though they may have deployed to different
# extents in the load segment where the generation technology did produce histroically.
L2233.StubTechProd_elec_cool_SW_USA %>%
filter(!grepl(gcamusa.DISALLOWED_COOLING_TECH, technology),
subs.share.weight == 0 & future.subs.shrwt > 0) %>%
mutate(from.year = min(MODEL_FUTURE_YEARS),
to.year = max(MODEL_YEARS),
interpolation.function = gcamusa.FIXED_SHAREWEIGHT,
to.value = gcamusa.DEFAULT_SHAREWEIGHT) %>%
rename(stub.technology = technology) %>%
mutate(apply.to = gcamusa.INTERP_APPLY_TO) %>%
select(region, supplysector, subsector0, subsector, stub.technology, apply.to,
from.year, to.year, to.value, interpolation.function) -> L2233.StubTechInterpTo_elecS_fut_USA
# Third, if a fuel and power plant combination did exist in the historical period,
# but switches to a new power plant type (i.e. Nuclear Gen 2 -> Gen 3), we assume
# that share weights of cooling technologies for that particular state remain similar
# to the old power plant (e.g. Gen 3 will have the same cooling tech share weights as Gen 2).
# Create a table with future techs whose cooling shares we can infer from existing ones
L2233.StubTechProd_elec_cool_SW_USA %>%
filter(!grepl(gcamusa.DISALLOWED_COOLING_TECH, technology),
subs.share.weight == 0 & future.subs.shrwt > 0) %>%
# Get rid of info related to calibrated values, which we've just confirmed are zero
select(-calOutputValue, -share.weight.year, -subs.share.weight, -tech.share.weight) %>%
# use semi_join to filter for future generation technologies which are mapped to current gen techs
semi_join(A23.elecS_tech_mapping_cool_shares_fut,
by = "subsector") %>%
left_join_error_no_match(A23.elecS_tech_mapping_cool_shares_fut,
by = "subsector") %>%
left_join_error_no_match(elec_tech_water_map %>%
select(to.technology, cooling_system),
by = c("technology" = "to.technology")) -> L2233.elec_cool_SW_future_techs_USA
# Create a table with existing techs whose cooling shares we can use to inform future ones
L2233.StubTechProd_elec_cool_SW_USA %>%
filter(!grepl(gcamusa.DISALLOWED_COOLING_TECH, technology)) %>%
# use semi_join to filter for current generation technologies which are used to inform
# future gen tech cooling shares
semi_join(A23.elecS_tech_mapping_cool_shares_fut,
by = c("subsector" = "mapped_subsector")) %>%
left_join_error_no_match(elec_tech_water_map %>%
select(to.technology, cooling_system),
by = c("technology" = "to.technology")) -> L2233.elec_cool_SW_mapped_techs_USA
# Join tables and match up share info
L2233.elec_cool_SW_future_techs_USA %>%
left_join_error_no_match(L2233.elec_cool_SW_mapped_techs_USA %>%
select(-technology, -future.subs.shrwt),
by = c("region", "supplysector", "subsector0", "year",
"mapped_subsector" = "subsector", "cooling_system")) %>%
group_by(region, supplysector, subsector0, subsector) %>%
# check if a generation tech has non-zero share-weight in any future period (i.e. sum > 0)
mutate(subs.share.weight = if_else(sum(calOutputValue) > 0, 1, 0)) %>%
# Remove any generation techs with zero generation by mapped technologies,
# which will result in zero shares for every cooling tech.
# This could happen if once through had 100% share historically, since
# once through is not included in this (future-oriented) table.
filter(subs.share.weight != 0) %>%
# calculate new cooling tech shares (share weights) without once through
mutate(share.weight = round(calOutputValue / sum(calOutputValue), energy.DIGITS_SHRWT)) %>%
ungroup() %>%
mutate(from.year = min(MODEL_FUTURE_YEARS),
to.year = max(MODEL_YEARS),
interpolation.function = gcamusa.FIXED_SHAREWEIGHT,
to.value = share.weight,
apply.to = gcamusa.INTERP_APPLY_TO) %>%
rename(stub.technology = technology) %>%
select(region, supplysector, subsector0, subsector, stub.technology, apply.to,
from.year, to.year, to.value, interpolation.function) -> L2233.StubTechInterpTo_elecS_mapped_USA
# Finally, all power plant and cooling technology combinations that do not exist in
# in future years are given 0 share weights in the future periods.
L2233.StubTechProd_elec_cool_SW_USA %>%
filter(future.subs.shrwt == 0) %>%
mutate(from.year = min(MODEL_FUTURE_YEARS),
to.year = max(MODEL_YEARS),
interpolation.function = gcamusa.FIXED_SHAREWEIGHT,
to.value = 0) %>%
rename(stub.technology = technology) %>%
mutate(apply.to = gcamusa.INTERP_APPLY_TO) %>%
select(region, supplysector, subsector0, subsector, stub.technology, apply.to,
from.year, to.year, to.value, interpolation.function) ->
L2233.StubTechInterpTo_elecS_nofut_USA
# Combine all "InterpTo" cases which specify a particular future shareweight value
L2233.StubTechInterpTo_elecS_oncethrough_USA %>%
bind_rows(L2233.StubTechInterpTo_elecS_fut_USA,
L2233.StubTechInterpTo_elecS_nofut_USA) %>%
# use anti-join to avoid duplicates, since the scope of L2233.StubTechInterpTo_elecS_mapped_USA
# overlaps with that of L2233.StubTechInterpTo_elecS_nofut_USA
anti_join(L2233.StubTechInterpTo_elecS_mapped_USA,
by = c("region", "supplysector", "subsector0", "subsector", "stub.technology")) %>%
bind_rows(L2233.StubTechInterpTo_elecS_mapped_USA) %>%
# use anti-join to remove any technologies which are fixed at calibration values
anti_join(L2233.StubTechInterp_elecS_cool_USA,
by = c("region", "supplysector", "subsector0", "subsector", "stub.technology")) ->
L2233.StubTechInterpTo_elecS_cool_USA
# Make a table with shareweights for start and end points of "InterpTo" rules
L2233.StubTechInterpTo_elecS_cool_USA %>%
gather(drop, year, from.year, to.year) %>%
select(region, supplysector, subsector0, subsector, stub.technology, year, share.weight = to.value) ->
L2233.StubTechShrwt_elecS_cool_USA
# Combine all interpolation cases
L2233.StubTechInterp_elecS_cool_USA %>%
bind_rows(L2233.StubTechInterpTo_elecS_cool_USA %>%
# get rid of to.value to consolidate to one table
# to.value is now reflected in L2233.StubTechShrwt_elecS_cool_USA
select(-to.value)) -> L2233.StubTechInterp_elecS_cool_USA
# Only done to manipulate variable and not throw an error
L2234.Supplysector_elecS_USA %>%
mutate(supplysector.1 = supplysector) %>%
select(-supplysector.1) ->
L2233.Supplysector_elecS_USA
# ===================================================
# Produce outputs
L2233.GlobalTechEff_elec_cool_USA %>%
add_title("Electricity Load Segments Technology Efficiencies") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Efficiencies") %>%
add_legacy_name("L2233.GlobalTechEff_elec_cool") %>%
add_precursors("L2234.GlobalTechEff_elecS_USA",
"L2241.GlobalTechEff_coal_vintage_USA",
"L2241.GlobalTechEff_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool",
"L2233.GlobalTechEff_elec_cool") ->
L2233.GlobalTechEff_elecS_cool_USA
L2233.GlobalTechShrwt_elec_cool_USA %>%
add_title("Electricity Load Segments Technology Shareweights") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Shareweights") %>%
add_legacy_name("L2233.GlobalTechShrwt_elec_cool") %>%
add_precursors("L2234.GlobalTechShrwt_elecS_USA",
"L2241.GlobalTechShrwt_coal_vintage_USA",
"L2241.GlobalTechShrwt_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool",
"L2233.GlobalTechShrwt_elec_cool") ->
L2233.GlobalTechShrwt_elecS_cool_USA
L2233.GlobalTechProfitShutdown_elec_cool_USA %>%
add_title("Electricity Load Segments Technology Profit Shutdown Decider") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Profit Shutdown Decider") %>%
add_legacy_name("L2233.GlobalTechProfitShutdown_elec_cool") %>%
add_precursors("L2234.GlobalTechProfitShutdown_elecS_USA",
"L2241.GlobalTechProfitShutdown_elec_coalret_USA",
"L2241.StubTechProfitShutdown_coal_vintage_USA",
"gcam-usa/A23.elecS_tech_mapping_cool",
"L2233.GlobalTechProfitShutdown_elec_cool") ->
L2233.GlobalTechProfitShutdown_elecS_cool_USA
L2233.GlobalTechOMvar_elec_USA %>%
add_title("Electricity Load Segments Technology Variable OM Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Variable OM Costs") %>%
add_legacy_name("L2233.GlobalTechOMvar_elec") %>%
add_precursors("L2234.GlobalTechOMvar_elecS_USA",
"L2241.GlobalTechOMvar_coal_vintage_USA",
"L2241.GlobalTechOMvar_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalTechOMvar_elecS_cool_USA
L2233.GlobalTechOMfixed_elec_USA %>%
add_title("Electricity Load Segments Technology Fixed OM Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Fixed OM Costs") %>%
add_legacy_name("L2233.GlobalTechOMfixed_elec") %>%
add_precursors("L2234.GlobalTechOMfixed_elecS_USA",
"L2241.GlobalTechOMfixed_coal_vintage_USA",
"L2241.GlobalTechOMfixed_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalTechOMfixed_elecS_cool_USA
L2233.GlobalTechCapital_elec_USA %>%
add_title("Electricity Load Segments Technology Capital Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Capital Costs") %>%
add_legacy_name("L2233.GlobalTechCapital_elec") %>%
add_precursors("L2234.GlobalTechCapital_elecS_USA",
"L2241.GlobalTechCapital_coal_vintage_USA",
"L2241.GlobalTechCapital_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalTechCapital_elecS_USA
L2233.GlobalTechCapital_elec_cool_USA %>%
add_title("Electricity Load Segments Technology Capital Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Capital Costs") %>%
add_legacy_name("L2233.GlobalTechCapital_elec_cool") %>%
add_precursors("L2234.GlobalTechCapital_elecS_USA",
"L2241.GlobalTechCapital_coal_vintage_USA",
"L2241.GlobalTechCapital_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool",
"L2233.GlobalTechCapital_elec_cool",
"L2233.GlobalTechCapital_elecPassthru") ->
L2233.GlobalTechCapital_elecS_cool_USA
L2233.GlobalTechCapFac_elec_USA %>%
add_title("Global Capacity Factors for Electricity Load Segments Technologies") %>%
add_units("none") %>%
add_comments("Global Capacity Factors for Electricity Load Segments Technologies") %>%
add_legacy_name("L2233.GlobalTechCapFac_elec") %>%
add_precursors("L2234.GlobalTechCapFac_elecS_USA",
"L2241.GlobalTechCapFac_coal_vintage_USA",
"L2241.GlobalTechCapFac_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalTechCapFac_elecS_cool_USA
L2233.GlobalTechSCurve_elecS_USA %>%
add_title("Electricity Load Segments Technology S-curve Shutdown Decider") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology S-curve Shutdown Decider") %>%
add_legacy_name("L2233.GlobalTechSCurve_elec") %>%
add_precursors("L2234.GlobalTechSCurve_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalTechSCurve_elecS_cool_USA
L2233.GlobalTechCoef_elecS_cool_USA %>%
add_title("Weighted water coefficients for reference scenario and load segment classification") %>%
add_units("none") %>%
add_comments("Weighted water coefficients for reference scenario and load segment classification") %>%
add_legacy_name("L2233.GlobalTechCoef_elec_cool") %>%
add_precursors("L2233.GlobalTechCoef_elec_cool",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalTechCoef_elecS_cool_USA
L2233.GlobalTechCapture_elecS_USA %>%
add_title("Electricity Load Segments CCS Technology Characteristics") %>%
add_units("none") %>%
add_comments("Electricity Load Segments CCS Technology Characteristics") %>%
add_legacy_name("L2233.GlobalTechCapture_elec") %>%
add_precursors("L2234.GlobalTechCapture_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool")->
L2233.GlobalTechCapture_elecS_cool_USA
L2233.GlobalTechLifetime_elecS_cool_USA %>%
add_title("Electricity Load Segments Lifetime") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Lifetime") %>%
add_legacy_name("L2233.GlobalTechLifetime_elec_cool") %>%
add_precursors("L2234.GlobalTechLifetime_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool")->
L2233.GlobalTechLifetime_elecS_cool_USA
L2233.AvgFossilEffKeyword_elecS_USA %>%
add_title("Average Fossil Efficiency Keywords for Electricity Load Segments Technologies") %>%
add_units("none") %>%
add_comments("Average Fossil Efficiency Keywords for Electricity Load Segments Technologies") %>%
add_legacy_name("L2233.AvgFossilEffKeyword_elec") %>%
add_precursors("L2234.AvgFossilEffKeyword_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.AvgFossilEffKeyword_elecS_cool_USA
L2233.GlobalIntTechBackup_elecS_USA %>%
add_title("Electricity Load Segments Intermittent Technology Backup Characteristics") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Backup Characteristics") %>%
add_legacy_name("L2233.GlobalIntTechBackup_elec") %>%
add_precursors("L2234.GlobalIntTechBackup_elecS_USA") ->
L2233.GlobalIntTechBackup_elecS_cool_USA
L2233.GlobalIntTechCapital_elecS_USA %>%
add_title("Electricity Load Segments Intermittent Technology Capital Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Capital Costs") %>%
add_legacy_name("L2233.GlobalIntTechCapital_elec") %>%
add_precursors("L2234.GlobalIntTechCapital_elecS_USA") ->
L2233.GlobalIntTechCapital_elecS_USA
L2233.GlobalIntTechCapital_elecS_cool_USA %>%
add_title("Electricity Load Segments Intermittent Technology Capital Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Capital Costs") %>%
add_legacy_name(" L2233.GlobalIntTechCapital_elec_cool") %>%
add_precursors("L2234.GlobalIntTechCapital_elecS_USA",
"L2233.GlobalIntTechCapital_elec_cool",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalIntTechCapital_elecS_cool_USA
L2233.GlobalIntTechEff_elecS_USA %>%
add_title("Electricity Load Segments Intermittent Technology Efficiencies") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Efficiencies") %>%
add_legacy_name("L2233.GlobalIntTechEff_elec") %>%
add_precursors("L2234.GlobalIntTechEff_elecS_USA") ->
L2233.GlobalIntTechEff_elecS_USA
L2233.GlobalIntTechEff_elecS_cool_USA %>%
add_title("Electricity Load Segments Intermittent Technology Efficiencies") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Efficiencies") %>%
add_legacy_name("L2233.GlobalIntTechEff_elec") %>%
add_precursors("L2234.GlobalIntTechEff_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool",
"L2233.GlobalIntTechEff_elec_cool") ->
L2233.GlobalIntTechEff_elecS_cool_USA
L2233.GlobalIntTechLifetime_elecS_cool_USA %>%
add_title("Electricity Load Segments Intermittent Technology Lifetimes") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Lifetimes") %>%
add_legacy_name("L2233.GlobalIntTechLifetime_elec_cool") %>%
add_precursors("L2234.GlobalIntTechLifetime_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalIntTechLifetime_elecS_cool_USA
L2233.GlobalIntTechOMfixed_elecS_cool_USA %>%
add_title("Electricity Load Segments Intermittent Technology Fixed OM Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Fixed OM Costs") %>%
add_legacy_name("L2233.GlobalIntTechOMfixed_elec_cool") %>%
add_precursors("L2234.GlobalIntTechOMfixed_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalIntTechOMfixed_elecS_cool_USA
L2233.GlobalIntTechOMvar_elecS_cool_USA %>%
add_title("Electricity Load Segments Intermittent Technology Variable OM Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Variable OM Costs") %>%
add_legacy_name("L2233.GlobalIntTechOMvar_elec_cool") %>%
add_precursors("L2234.GlobalIntTechOMvar_elecS_USA") ->
L2233.GlobalIntTechOMvar_elecS_cool_USA
L2233.GlobalIntTechShrwt_elecS_cool_USA %>%
add_title("Electricity Load Segments Intermittent Technology Shareweights") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Shareweights") %>%
add_legacy_name("L2233.GlobalIntTechShrwt_elec_cool") %>%
add_precursors("L2234.GlobalIntTechShrwt_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalIntTechShrwt_elecS_cool_USA
L2233.GlobalIntTechCoef_elecS_cool_USA %>%
add_title("Water demand coefs for int techs") %>%
add_units("none") %>%
add_comments("Water demand coefs for int techs") %>%
add_legacy_name("L2233.GlobalIntTechCoef_elec_cool") %>%
add_precursors("L2233.GlobalIntTechCoef_elec_cool",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalIntTechCoef_elecS_cool_USA
L2233.PrimaryRenewKeyword_elecS_cool_USA %>%
add_title("Primary Renewable Keywords for Electricity Load Segments Technologies") %>%
add_units("none") %>%
add_comments("Primary Renewable Keywords for Electricity Load Segments Technologies") %>%
add_legacy_name("L2233.PrimaryRenewKeyword_elec_cool") %>%
add_precursors("L2234.PrimaryRenewKeyword_elecS_USA") ->
L2233.PrimaryRenewKeyword_elecS_cool_USA
L2233.PrimaryRenewKeywordInt_elecS_cool_USA %>%
add_title("Primary Renewable Keywords for Electricity Load Segments Intermittent Technologies") %>%
add_units("none") %>%
add_comments("Primary Renewable Keywords for Electricity Load Segments Intermittent Technologies") %>%
add_legacy_name("L2233.PrimaryRenewKeywordInt_elec_cool") %>%
add_precursors("L2234.PrimaryRenewKeywordInt_elecS_USA") ->
L2233.PrimaryRenewKeywordInt_elecS_cool_USA
L2233.StubTechEff_elec_USA %>%
add_title("Electricity Load Segments Base Year Efficiencies") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Base Year Efficiencies") %>%
add_legacy_name("L2233.StubTechEff_elec") %>%
add_precursors("L2234.StubTechEff_elecS_USA",
"L2241.StubTechEff_coal_vintage_USA",
"L2241.StubTechEff_elec_coalret_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechEff_elecS_cool_USA
L2233.StubTechCoef_elecS_cool_USA %>%
add_title("Water demand coefficients at state level for Electricity Load Segments") %>%
add_units("none") %>%
add_comments("Water demand coefficients at state level for Electricity Load Segments") %>%
add_legacy_name("L2233.StubTechCoef_elec") %>%
add_precursors("L2233.GlobalTechCoef_elec_cool",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechCoef_elecS_cool_USA
L2233.StubTechMarket_elec_USA %>%
add_title("Energy Inputs for Electricity Load Segments and associated Cooling Technologies") %>%
add_units("none") %>%
add_comments("Energy Inputs for Electricity Load Segments and associated Cooling Technologies") %>%
add_legacy_name("L2233.StubTechMarket_elec") %>%
add_precursors("L2234.StubTechMarket_elecS_USA",
"L2241.StubTechMarket_coal_vintage_USA",
"L2241.StubTechMarket_elec_coalret_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechMarket_elecS_cool_USA
L2233.StubTechProd_elec_USA %>%
add_title("Electricity Load Segments and Cooling Technology Calibration Outputs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments and Cooling Technology Calibration Outputs") %>%
add_legacy_name("L2233.StubTechProd_elec") %>%
add_precursors("L2234.StubTechProd_elecS_USA",
"L2241.StubTechProd_coal_vintage_USA",
"L2241.StubTechProd_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool",
"L1233.out_EJ_state_elec_F_tech_cool",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/elec_tech_water_map") ->
L2233.StubTechProd_elecS_cool_USA
L2233.StubTechSCurve_elec_USA %>%
add_title("Electricity Load Segment and Cooling Technology S-Curves") %>%
add_units("none") %>%
add_comments("Electricity Load Segment and Cooling Technology S-Curves") %>%
add_legacy_name("L2233.StubTechSCurve_elec") %>%
add_precursors("L2241.StubTechSCurve_coal_vintage_USA",
"L2241.StubTechSCurve_elec_coalret_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechSCurve_elecS_cool_USA
L2233.StubTechProfitShutdown_elecS_cool_USA %>%
add_title("Electricity Load Segment and Cooling Technology Profit Shutdown Decider") %>%
add_units("none") %>%
add_comments("Electricity Load Segment and Cooling Technology Profit Shutdown Decider") %>%
add_legacy_name("L2233.StubTechSCurve_elec") %>%
add_precursors("L2241.StubTechProfitShutdown_coal_vintage_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechProfitShutdown_elecS_cool_USA
L2233.StubTechCapFactor_elecS_solar_USA %>%
add_title("State-specific Capacity Factors for Electricity Load Segments Solar and Cooling Technologies") %>%
add_units("none") %>%
add_comments("State-specific Capacity Factors for Electricity Load Segments Solar and Cooling Technologies") %>%
add_legacy_name("L2233.StubTechCapFactor_elec_solar") %>%
add_precursors("L2234.StubTechCapFactor_elecS_solar_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechCapFactor_elecS_solar_USA
L2233.StubTechCapFactor_elecS_wind_USA %>%
add_title("State-specific Capacity Factors for Electricity Load Segments Wind Technologies") %>%
add_units("none") %>%
add_comments("State-specific Capacity Factors for Electricity Load Segments Wind Technologies") %>%
add_legacy_name("L2233.StubTechCapFactor_elec_wind") %>%
add_precursors("L2234.StubTechCapFactor_elecS_wind_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechCapFactor_elecS_wind_USA
L2233.StubTechElecMarket_backup_elecS_USA %>%
add_title("Electricity Load Segments Sector Name for Backup Markets") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Sector Name for Backup Markets") %>%
add_legacy_name("L2233.StubTechElecMarket_backup_elec") %>%
add_precursors("L2234.StubTechElecMarket_backup_elecS_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechElecMarket_backup_elecS_cool_USA
L2233.StubTechFixOut_elecS_USA %>%
add_title("Electricity Load Segments Fixed Outputs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Fixed Outputs") %>%
add_legacy_name("L2233.StubTechFixOut_elec") %>%
add_precursors("L2234.StubTechFixOut_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechFixOut_elecS_cool_USA
L2233.StubTechFixOut_hydro_elecS_USA %>%
add_title("Electricity Load Segments Hydro Fixed Outputs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Hydro Fixed Outputs") %>%
add_legacy_name("L2233.StubTechFixOut_hydro_elec") %>%
add_precursors("L2234.StubTechFixOut_hydro_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechFixOut_hydro_elecS_cool_USA
L2233.StubTechCost_offshore_wind_elecS_USA %>%
add_title("Electricity Load Segments Offshore Wind Cost Adjustment") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Offshore Wind Cost Adjustment") %>%
add_legacy_name("L2233.StubTechCost_offshore_wind_elec_USA") %>%
add_precursors("L2234.StubTechCost_offshore_wind_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechCost_offshore_wind_elecS_cool_USA
L2233.StubTechMarket_backup_elecS_USA %>%
add_title("Backup Energy Inputs for Electricity Load Segments Intermittent Technologies") %>%
add_units("none") %>%
add_comments("Backup Energy Inputs for Electricity Load Segments Intermittent Technologies") %>%
add_legacy_name("L2233.StubTechMarket_backup_elec") %>%
add_precursors("L2234.StubTechMarket_backup_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechMarket_backup_elecS_cool_USA
L2233.StubTechInterp_elecS_cool_USA %>%
add_title("Electricity Load Segments Stub Tech Interpolation Rules") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Stub Tech Interpolation Rules - fixed at calibration values") %>%
add_legacy_name("L2233.StubTechShrwt_elec") %>%
same_precursors_as(L2233.StubTechProd_elec_USA) %>%
same_precursors_as(L2233.SubsectorShrwt_elecS_cool_USA) %>%
add_precursors("gcam-usa/A23.elecS_tech_mapping_cool_shares_fut") ->
L2233.StubTechInterp_elecS_cool_USA
L2233.StubTechShrwt_elecS_cool_USA %>%
add_title("Electricity Load Segments Cooling Technology Stub Tech Shareweights") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Cooling Technology Stub Tech Shareweights") %>%
add_legacy_name("L2233.StubTechShrwt_elec") %>%
same_precursors_as(L2233.StubTechInterp_elecS_cool_USA) ->
L2233.StubTechShrwt_elecS_cool_USA
L2233.SubsectorLogit_elecS_USA %>%
add_title("Nested Subsector Information for Horizontal Electricity Load Segments",overwrite=TRUE) %>%
add_units("none") %>%
add_comments("Nested Subsector Information for Horizontal Electricity Load Segments") %>%
add_legacy_name("L223.SubsectorLogit_elec") %>%
add_precursors("L2234.SubsectorLogit_elecS_USA") ->
L2233.SubsectorLogit_elecS_USA
L2233.SubsectorLogit_elecS_cool_USA %>%
add_title("Subsector Information for Horizontal Electricity Load Segments with Cooling Technologies",overwrite=TRUE) %>%
add_units("none") %>%
add_comments("Subsector Information for Horizontal Electricity Load Segments with Cooling Technologies") %>%
add_legacy_name("L2233.SubsectorLogit_elec_cool") %>%
add_precursors("L2234.SubsectorLogit_elecS_USA") ->
L2233.SubsectorLogit_elecS_cool_USA
L2233.SubsectorShrwt_elecS_USA %>%
add_title("Nested Electricity Load Segments Subsector Shareweights") %>%
add_units("none") %>%
add_comments("Nested Electricity Load Segments Subsector Shareweights") %>%
add_legacy_name("L2233.SubsectorShrwt_elec") %>%
add_precursors("L2234.SubsectorShrwt_elecS_USA") ->
L2233.SubsectorShrwt_elecS_USA
L2233.SubsectorShrwt_elecS_cool_USA %>%
add_title("Electricity Load Segments and Cooling Technology Subsector Shareweights") %>%
add_units("none") %>%
add_comments("Electricity Load Segments and Cooling Technology Subsector Shareweights") %>%
add_legacy_name("L2233.SubsectorShrwt_elec") %>%
add_precursors("L2234.StubTechProd_elecS_USA") ->
L2233.SubsectorShrwt_elecS_cool_USA
L2233.SubsectorShrwtInterp_elecS_USA %>%
add_title("Electricity Load Segments Nesting-Subsector Shareweight Interpolation") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Nesting-Subsector Shareweight Interpolation") %>%
add_legacy_name("L2233.SubsectorShrwtInterp_elec") %>%
add_precursors("L2234.SubsectorShrwtInterp_elecS_USA") ->
L2233.SubsectorShrwtInterp_elecS_USA
L2233.SubsectorShrwtInterpTo_elecS_USA %>%
add_title("Electricity Load Segments Nesting-Subsector Shareweight Interpolation") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Nesting-Subsector Shareweight Interpolation") %>%
add_legacy_name("L2233.SubsectorShrwtInterpTo_elec") %>%
add_precursors("L2234.SubsectorShrwtInterpTo_elecS_USA") ->
L2233.SubsectorShrwtInterpTo_elecS_USA
L2233.Supplysector_elecS_USA %>%
add_title("Supply Sector Information for Electricity Load Segments") %>%
add_units("none") %>%
add_comments("Supply Sector Information for Electricity Load Segments") %>%
add_legacy_name("L2233.Supplysector_elec") %>%
add_precursors("L2234.Supplysector_elecS_USA") ->
L2233.Supplysector_elecS_cool_USA
return_data(L2233.GlobalTechEff_elecS_cool_USA,
L2233.GlobalTechShrwt_elecS_cool_USA,
L2233.GlobalTechProfitShutdown_elecS_cool_USA,
L2233.GlobalTechOMvar_elecS_cool_USA,
L2233.GlobalTechOMfixed_elecS_cool_USA,
L2233.GlobalTechCapital_elecS_USA,
L2233.GlobalTechCapital_elecS_cool_USA,
L2233.GlobalTechCapFac_elecS_cool_USA,
L2233.GlobalTechSCurve_elecS_cool_USA,
L2233.GlobalTechCoef_elecS_cool_USA,
L2233.GlobalTechCapture_elecS_cool_USA,
L2233.GlobalTechLifetime_elecS_cool_USA,
L2233.AvgFossilEffKeyword_elecS_cool_USA,
L2233.GlobalIntTechBackup_elecS_cool_USA,
L2233.GlobalIntTechCapital_elecS_USA,
L2233.GlobalIntTechCapital_elecS_cool_USA,
L2233.GlobalIntTechEff_elecS_USA,
L2233.GlobalIntTechEff_elecS_cool_USA,
L2233.GlobalIntTechLifetime_elecS_cool_USA,
L2233.GlobalIntTechOMfixed_elecS_cool_USA,
L2233.GlobalIntTechOMvar_elecS_cool_USA,
L2233.GlobalIntTechShrwt_elecS_cool_USA,
L2233.GlobalIntTechCoef_elecS_cool_USA,
L2233.PrimaryRenewKeyword_elecS_cool_USA,
L2233.PrimaryRenewKeywordInt_elecS_cool_USA,
L2233.StubTechEff_elecS_cool_USA,
L2233.StubTechCoef_elecS_cool_USA,
L2233.StubTechMarket_elecS_cool_USA,
L2233.StubTechProd_elecS_cool_USA,
L2233.StubTechSCurve_elecS_cool_USA,
L2233.StubTechCapFactor_elecS_solar_USA,
L2233.StubTechCapFactor_elecS_wind_USA,
L2233.StubTechElecMarket_backup_elecS_cool_USA,
L2233.StubTechFixOut_elecS_cool_USA,
L2233.StubTechFixOut_hydro_elecS_cool_USA,
L2233.StubTechMarket_backup_elecS_cool_USA,
L2233.StubTechProfitShutdown_elecS_cool_USA,
L2233.StubTechShrwt_elecS_cool_USA,
L2233.StubTechInterp_elecS_cool_USA,
L2233.SubsectorLogit_elecS_USA,
L2233.SubsectorLogit_elecS_cool_USA,
L2233.SubsectorShrwt_elecS_USA,
L2233.SubsectorShrwt_elecS_cool_USA,
L2233.SubsectorShrwtInterp_elecS_USA,
L2233.StubTechCost_offshore_wind_elecS_cool_USA,
L2233.SubsectorShrwtInterpTo_elecS_USA,
L2233.Supplysector_elecS_cool_USA)
} else {
stop("Unknown command")
}
}
JGCRI/gcamdata documentation built on March 21, 2023, 2:19 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions module_gcamusa_LA2233.elec_segments_water_USA
Documented in module_gcamusa_LA2233.elec_segments_water_USA
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_gcamusa_LA2233.elec_segments_water_USA
#'
#' Generates GCAM-USA model inputs for multiple load segments electricity sector and cooling systems by state.
#'
#' @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{L2233.GlobalTechEff_elecS_cool_USA}, \code{L2233.GlobalTechShrwt_elecS_cool_USA}, \code{L2233.GlobalTechProfitShutdown_elecS_cool_USA},
#' \code{L2233.GlobalTechOMvar_elecS_cool_USA}, \code{L2233.GlobalTechOMfixed_elecS_cool_USA}, \code{L2233.GlobalTechCapital_elecS_USA}, \code{L2233.GlobalTechCapital_elecS_cool_USA},
#' \code{L2233.GlobalTechCapFac_elecS_cool_USA}, \code{L2233.GlobalTechSCurve_elecS_cool_USA}, \code{L2233.GlobalTechCoef_elecS_cool_USA}, \code{L2233.GlobalTechCapture_elecS_cool_USA},
#' \code{L2233.GlobalTechLifetime_elecS_cool_USA}, \code{L2233.AvgFossilEffKeyword_elecS_cool_USA}, \code{L2233.GlobalIntTechBackup_elecS_cool_USA}, \code{L2233.GlobalIntTechCapital_elecS_USA},
#' \code{L2233.GlobalIntTechCapital_elecS_cool_USA}, \code{L2233.GlobalIntTechEff_elecS_USA}, \code{L2233.GlobalIntTechEff_elecS_cool_USA}, \code{L2233.GlobalIntTechLifetime_elecS_cool_USA},
#' \code{L2233.GlobalIntTechOMfixed_elecS_cool_USA}, \code{L2233.GlobalIntTechOMvar_elecS_cool_USA}, \code{L2233.GlobalIntTechShrwt_elecS_cool_USA}, \code{L2233.GlobalIntTechCoef_elecS_cool_USA},
#' \code{L2233.PrimaryRenewKeyword_elecS_cool_USA}, \code{L2233.PrimaryRenewKeywordInt_elecS_cool_USA}, \code{L2233.StubTechEff_elecS_cool_USA}, \code{L2233.StubTechCoef_elecS_cool_USA},
#' \code{L2233.StubTechMarket_elecS_cool_USA}, \code{L2233.StubTechProd_elecS_cool_USA}, \code{L2233.StubTechSCurve_elecS_cool_USA}, \code{L2233.StubTechCapFactor_elecS_solar_USA},
#' \code{L2233.StubTechCapFactor_elecS_wind_USA}, \code{L2233.StubTechElecMarket_backup_elecS_cool_USA}, \code{L2233.StubTechFixOut_elecS_cool_USA}, \code{L2233.StubTechFixOut_hydro_elecS_cool_USA},
#' \code{L2233.StubTechMarket_backup_elecS_cool_USA}, \code{L2233.StubTechProfitShutdown_elecS_cool_USA}, \code{L2233.StubTechShrwt_elecS_cool_USA}, \code{L2233.StubTechInterp_elecS_cool_USA},
#' \code{L2233.StubTechCost_offshore_wind_elecS_cool_USA}, \code{L2233.SubsectorLogit_elecS_USA}, \code{L2233.SubsectorLogit_elecS_cool_USA}, \code{L2233.SubsectorShrwt_elecS_USA},
#' \code{L2233.SubsectorShrwt_elecS_cool_USA}, \code{L2233.SubsectorShrwtInterp_elecS_USA}, \code{L2233.SubsectorShrwtInterpTo_elecS_USA}, \code{L2233.Supplysector_elecS_cool_USA}.
#' The corresponding file in the original data system was \code{LA2233.electricity_water_USA} (gcam-usa level2)
#' @details This chunk generates input files to create an electricity generation sector with multiple load segments
#' for each state and creates the demand by load, fuel, power plant, and cooling system type.
#' @importFrom assertthat assert_that
#' @importFrom dplyr anti_join distinct filter if_else mutate select semi_join summarise_if bind_rows
#' @importFrom tidyr complete nesting replace_na
#' @author NTG May 2020
module_gcamusa_LA2233.elec_segments_water_USA <- function(command, ...) {
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "gcam-usa/A23.elecS_tech_mapping_cool",
FILE = "gcam-usa/elec_tech_water_map",
FILE = "gcam-usa/A23.elecS_tech_mapping_cool_shares_fut",
FILE = "gcam-usa/usa_seawater_states_basins",
"L1233.out_EJ_state_elec_F_tech_cool",
"L2233.GlobalTechEff_elec_cool",
"L2233.GlobalTechShrwt_elec_cool",
"L2233.GlobalTechProfitShutdown_elec_cool",
"L2233.GlobalTechCapital_elec_cool",
"L2233.GlobalTechCapital_elecPassthru",
"L2233.GlobalTechCoef_elec_cool",
"L2233.GlobalIntTechCapital_elec_cool",
"L2233.GlobalIntTechEff_elec_cool",
"L2233.GlobalIntTechCoef_elec_cool",
"L2234.AvgFossilEffKeyword_elecS_USA",
"L2234.GlobalIntTechBackup_elecS_USA",
"L2234.GlobalIntTechCapital_elecS_USA",
"L2234.GlobalIntTechEff_elecS_USA",
"L2234.GlobalIntTechLifetime_elecS_USA",
"L2234.GlobalIntTechOMfixed_elecS_USA",
"L2234.GlobalIntTechOMvar_elecS_USA",
"L2234.GlobalIntTechShrwt_elecS_USA",
"L2234.GlobalTechCapFac_elecS_USA",
"L2234.GlobalTechCapital_elecS_USA",
"L2234.GlobalTechCapture_elecS_USA",
"L2234.GlobalTechEff_elecS_USA",
"L2234.GlobalTechLifetime_elecS_USA",
"L2234.GlobalTechOMfixed_elecS_USA",
"L2234.GlobalTechOMvar_elecS_USA",
"L2234.GlobalTechProfitShutdown_elecS_USA",
"L2234.GlobalTechSCurve_elecS_USA",
"L2234.GlobalTechShrwt_elecS_USA",
"L2234.PrimaryRenewKeyword_elecS_USA",
"L2234.PrimaryRenewKeywordInt_elecS_USA",
"L2234.StubTechCapFactor_elecS_solar_USA",
"L2234.StubTechCapFactor_elecS_wind_USA",
"L2234.StubTechEff_elecS_USA",
"L2234.StubTechElecMarket_backup_elecS_USA",
"L2234.StubTechFixOut_elecS_USA",
"L2234.StubTechFixOut_hydro_elecS_USA",
"L2234.StubTechMarket_backup_elecS_USA",
"L2234.StubTechMarket_elecS_USA",
"L2234.StubTechProd_elecS_USA",
"L2234.SubsectorLogit_elecS_USA",
"L2234.SubsectorShrwt_elecS_USA",
"L2234.SubsectorShrwtInterp_elecS_USA",
"L2234.SubsectorShrwtInterpTo_elecS_USA",
"L2234.Supplysector_elecS_USA",
"L2234.StubTechCost_offshore_wind_elecS_USA",
"L2241.GlobalTechCapFac_elec_coalret_USA",
"L2241.GlobalTechCapital_elec_coalret_USA",
"L2241.GlobalTechEff_elec_coalret_USA",
"L2241.GlobalTechOMfixed_elec_coalret_USA",
"L2241.GlobalTechOMvar_elec_coalret_USA",
"L2241.GlobalTechProfitShutdown_elec_coalret_USA",
"L2241.GlobalTechShrwt_elec_coalret_USA",
"L2241.StubTechEff_elec_coalret_USA",
"L2241.StubTechMarket_elec_coalret_USA",
"L2241.StubTechProd_elec_coalret_USA",
"L2241.StubTechSCurve_elec_coalret_USA",
"L2241.GlobalTechCapFac_coal_vintage_USA",
"L2241.GlobalTechCapital_coal_vintage_USA",
"L2241.GlobalTechEff_coal_vintage_USA",
"L2241.GlobalTechOMfixed_coal_vintage_USA",
"L2241.GlobalTechOMvar_coal_vintage_USA",
"L2241.GlobalTechShrwt_coal_vintage_USA",
"L2241.StubTechEff_coal_vintage_USA",
"L2241.StubTechMarket_coal_vintage_USA",
"L2241.StubTechProd_coal_vintage_USA",
"L2241.StubTechProfitShutdown_coal_vintage_USA",
"L2241.StubTechSCurve_coal_vintage_USA"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L2233.GlobalTechEff_elecS_cool_USA",
"L2233.GlobalTechShrwt_elecS_cool_USA",
"L2233.GlobalTechProfitShutdown_elecS_cool_USA",
"L2233.GlobalTechOMvar_elecS_cool_USA",
"L2233.GlobalTechOMfixed_elecS_cool_USA",
"L2233.GlobalTechCapital_elecS_USA",
"L2233.GlobalTechCapital_elecS_cool_USA",
"L2233.GlobalTechCapFac_elecS_cool_USA",
"L2233.GlobalTechSCurve_elecS_cool_USA",
"L2233.GlobalTechCoef_elecS_cool_USA",
"L2233.GlobalTechCapture_elecS_cool_USA",
"L2233.GlobalTechLifetime_elecS_cool_USA",
"L2233.AvgFossilEffKeyword_elecS_cool_USA",
"L2233.GlobalIntTechBackup_elecS_cool_USA",
"L2233.GlobalIntTechCapital_elecS_USA",
"L2233.GlobalIntTechCapital_elecS_cool_USA",
"L2233.GlobalIntTechEff_elecS_USA",
"L2233.GlobalIntTechEff_elecS_cool_USA",
"L2233.GlobalIntTechLifetime_elecS_cool_USA",
"L2233.GlobalIntTechOMfixed_elecS_cool_USA",
"L2233.GlobalIntTechOMvar_elecS_cool_USA",
"L2233.GlobalIntTechShrwt_elecS_cool_USA",
"L2233.GlobalIntTechCoef_elecS_cool_USA",
"L2233.PrimaryRenewKeyword_elecS_cool_USA",
"L2233.PrimaryRenewKeywordInt_elecS_cool_USA",
"L2233.StubTechEff_elecS_cool_USA",
"L2233.StubTechCoef_elecS_cool_USA",
"L2233.StubTechMarket_elecS_cool_USA",
"L2233.StubTechProd_elecS_cool_USA",
"L2233.StubTechSCurve_elecS_cool_USA",
"L2233.StubTechCapFactor_elecS_solar_USA",
"L2233.StubTechCapFactor_elecS_wind_USA",
"L2233.StubTechElecMarket_backup_elecS_cool_USA",
"L2233.StubTechFixOut_elecS_cool_USA",
"L2233.StubTechFixOut_hydro_elecS_cool_USA",
"L2233.StubTechMarket_backup_elecS_cool_USA",
"L2233.StubTechProfitShutdown_elecS_cool_USA",
"L2233.StubTechShrwt_elecS_cool_USA",
"L2233.StubTechInterp_elecS_cool_USA",
"L2233.StubTechCost_offshore_wind_elecS_cool_USA",
"L2233.SubsectorLogit_elecS_USA",
"L2233.SubsectorLogit_elecS_cool_USA",
"L2233.SubsectorShrwt_elecS_USA",
"L2233.SubsectorShrwt_elecS_cool_USA",
"L2233.SubsectorShrwtInterp_elecS_USA",
"L2233.SubsectorShrwtInterpTo_elecS_USA",
"L2233.Supplysector_elecS_cool_USA"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
region<- supplysector <- subsector <- technology <- year <- minicam.energy.input <-
coefficient<- market.name <- Electric.sector <- Electric.sector.intermittent.technology <-
intermittent.technology <- subsector_1 <- sector <- fuel <- Electric.sector.technology <-
water_sector <- water_type <- state <- state_name <- ':=' <- x <- plant_type <- State <-
value <- Basin_name <- Electric.sector <- Electric.sector.technology <-
apply.to <- GCAM_basin_ID <- basin_name <- calOutputValue <- capital.overnight <-
cooling_system <- deflator <- efficiency <- fixed.charge.rate <- from.subsector <-
from.supplysector <- from.technology <- from.year <- global.share.weight <-
input.capital <- input.cost <- input.unit <- intensity_CORE <-
intermittent.technology <- interpolation.function <- loadfactor_CORE <-
logit.exponent <- logit.type <- logit.year.fillout <- median.shutdown.point <-
non_fuel_cost_core <- out_MWh.sea <- out_MWh_sea <- output.unit <-
passthrough.sector <- plant_type <- price.unit <- region <- sce <- sector.name <- share <-
share.weight <- share.weight.sum <- share.weight.year <- share_nat.sea <- state <-
state.cooling.share.weight <- state.to.country.share <- state_abbr <-
stub.technology <- subs.share.weight <- subsector <- subsector.1 <-
subsector.name <- subsector.name0 <- subsector0 <- subsector_1 <- supplysector <-
supplysector.1 <- tag <- tech.share.weight <- technology <- technology.x <-
technology.y <- to.subsector <- to.supplysector <- to.technology <- to.value <-
to.year <- updated.share.weight <- value <- volume <- water_sector <- water_type <-
weight_EJ_core <- wt_short <- year <- GLU_name <- future.subs.shrwt <- hist.share <- NULL
# ===================================================
# 1. Read files
# Load required inputs
A23.elecS_tech_mapping_cool <- get_data(all_data, "gcam-usa/A23.elecS_tech_mapping_cool", strip_attributes = TRUE)
elec_tech_water_map <- get_data(all_data, "gcam-usa/elec_tech_water_map", strip_attributes = TRUE)
A23.elecS_tech_mapping_cool_shares_fut <- get_data(all_data, "gcam-usa/A23.elecS_tech_mapping_cool_shares_fut", strip_attributes = TRUE)
usa_seawater_states_basins <- get_data(all_data, "gcam-usa/usa_seawater_states_basins", strip_attributes = TRUE)
L1233.out_EJ_state_elec_F_tech_cool <- get_data(all_data, "L1233.out_EJ_state_elec_F_tech_cool", strip_attributes = TRUE)
L2233.GlobalTechEff_elec_cool <- get_data(all_data, "L2233.GlobalTechEff_elec_cool", strip_attributes = TRUE)
L2233.GlobalTechShrwt_elec_cool <- get_data(all_data, "L2233.GlobalTechShrwt_elec_cool", strip_attributes = TRUE)
L2233.GlobalTechProfitShutdown_elec_cool <- get_data(all_data, "L2233.GlobalTechProfitShutdown_elec_cool", strip_attributes = TRUE)
L2233.GlobalTechCapital_elec_cool <- get_data(all_data, "L2233.GlobalTechCapital_elec_cool", strip_attributes = TRUE)
L2233.GlobalTechCapital_elecPassthru <- get_data(all_data, "L2233.GlobalTechCapital_elecPassthru", strip_attributes = TRUE)
L2233.GlobalTechCoef_elec_cool <- get_data(all_data, "L2233.GlobalTechCoef_elec_cool", strip_attributes = TRUE)
L2233.GlobalIntTechCapital_elec_cool <- get_data(all_data, "L2233.GlobalIntTechCapital_elec_cool", strip_attributes = TRUE)
L2233.GlobalIntTechEff_elec_cool <- get_data(all_data, "L2233.GlobalIntTechEff_elec_cool", strip_attributes = TRUE)
L2233.GlobalIntTechCoef_elec_cool <- get_data(all_data, "L2233.GlobalIntTechCoef_elec_cool", strip_attributes = TRUE)
L2234.AvgFossilEffKeyword_elecS_USA <- get_data(all_data, "L2234.AvgFossilEffKeyword_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechBackup_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechBackup_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechCapital_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechCapital_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechEff_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechEff_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechLifetime_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechLifetime_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechOMfixed_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechOMfixed_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechOMvar_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechOMvar_elecS_USA", strip_attributes = TRUE)
L2234.GlobalIntTechShrwt_elecS_USA <- get_data(all_data,"L2234.GlobalIntTechShrwt_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechCapFac_elecS_USA <- get_data(all_data,"L2234.GlobalTechCapFac_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechCapital_elecS_USA <- get_data(all_data,"L2234.GlobalTechCapital_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechCapture_elecS_USA <- get_data(all_data,"L2234.GlobalTechCapture_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechEff_elecS_USA <- get_data(all_data,"L2234.GlobalTechEff_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechLifetime_elecS_USA <- get_data(all_data,"L2234.GlobalTechLifetime_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechOMfixed_elecS_USA <- get_data(all_data,"L2234.GlobalTechOMfixed_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechOMvar_elecS_USA <- get_data(all_data,"L2234.GlobalTechOMvar_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechProfitShutdown_elecS_USA <- get_data(all_data,"L2234.GlobalTechProfitShutdown_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechSCurve_elecS_USA <- get_data(all_data,"L2234.GlobalTechSCurve_elecS_USA", strip_attributes = TRUE)
L2234.GlobalTechShrwt_elecS_USA <- get_data(all_data,"L2234.GlobalTechShrwt_elecS_USA", strip_attributes = TRUE)
L2234.PrimaryRenewKeyword_elecS_USA <- get_data(all_data,"L2234.PrimaryRenewKeyword_elecS_USA", strip_attributes = TRUE)
L2234.PrimaryRenewKeywordInt_elecS_USA <- get_data(all_data,"L2234.PrimaryRenewKeywordInt_elecS_USA", strip_attributes = TRUE)
L2234.StubTechCapFactor_elecS_solar_USA <- get_data(all_data,"L2234.StubTechCapFactor_elecS_solar_USA", strip_attributes = TRUE)
L2234.StubTechCapFactor_elecS_wind_USA <- get_data(all_data,"L2234.StubTechCapFactor_elecS_wind_USA", strip_attributes = TRUE)
L2234.StubTechEff_elecS_USA <- get_data(all_data,"L2234.StubTechEff_elecS_USA", strip_attributes = TRUE)
L2234.StubTechElecMarket_backup_elecS_USA <- get_data(all_data,"L2234.StubTechElecMarket_backup_elecS_USA", strip_attributes = TRUE)
L2234.StubTechFixOut_elecS_USA <- get_data(all_data,"L2234.StubTechFixOut_elecS_USA", strip_attributes = TRUE)
L2234.StubTechFixOut_hydro_elecS_USA <- get_data(all_data,"L2234.StubTechFixOut_hydro_elecS_USA", strip_attributes = TRUE)
L2234.StubTechMarket_backup_elecS_USA <- get_data(all_data,"L2234.StubTechMarket_backup_elecS_USA", strip_attributes = TRUE)
L2234.StubTechMarket_elecS_USA <- get_data(all_data,"L2234.StubTechMarket_elecS_USA", strip_attributes = TRUE)
L2234.StubTechProd_elecS_USA <- get_data(all_data,"L2234.StubTechProd_elecS_USA", strip_attributes = TRUE)
L2234.SubsectorLogit_elecS_USA <- get_data(all_data,"L2234.SubsectorLogit_elecS_USA", strip_attributes = TRUE)
L2234.SubsectorShrwt_elecS_USA <- get_data(all_data,"L2234.SubsectorShrwt_elecS_USA", strip_attributes = TRUE)
L2234.SubsectorShrwtInterp_elecS_USA <- get_data(all_data,"L2234.SubsectorShrwtInterp_elecS_USA", strip_attributes = TRUE)
L2234.SubsectorShrwtInterpTo_elecS_USA <- get_data(all_data,"L2234.SubsectorShrwtInterpTo_elecS_USA", strip_attributes = TRUE)
L2234.Supplysector_elecS_USA <- get_data(all_data,"L2234.Supplysector_elecS_USA", strip_attributes = TRUE)
L2234.StubTechCost_offshore_wind_elecS_USA <- get_data(all_data,"L2234.StubTechCost_offshore_wind_elecS_USA", strip_attributes = TRUE)
L2241.GlobalTechCapFac_elec_coalret_USA <- get_data(all_data, "L2241.GlobalTechCapFac_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechCapital_elec_coalret_USA <- get_data(all_data,"L2241.GlobalTechCapital_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechEff_elec_coalret_USA <- get_data(all_data,"L2241.GlobalTechEff_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechOMfixed_elec_coalret_USA <- get_data(all_data,"L2241.GlobalTechOMfixed_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechOMvar_elec_coalret_USA <- get_data(all_data,"L2241.GlobalTechOMvar_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechProfitShutdown_elec_coalret_USA <- get_data(all_data,"L2241.GlobalTechProfitShutdown_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechShrwt_elec_coalret_USA <- get_data(all_data,"L2241.GlobalTechShrwt_elec_coalret_USA", strip_attributes = TRUE)
L2241.StubTechEff_elec_coalret_USA <- get_data(all_data,"L2241.StubTechEff_elec_coalret_USA", strip_attributes = TRUE)
L2241.StubTechMarket_elec_coalret_USA <- get_data(all_data,"L2241.StubTechMarket_elec_coalret_USA", strip_attributes = TRUE)
L2241.StubTechProd_elec_coalret_USA <- get_data(all_data,"L2241.StubTechProd_elec_coalret_USA", strip_attributes = TRUE)
L2241.StubTechSCurve_elec_coalret_USA <- get_data(all_data,"L2241.StubTechSCurve_elec_coalret_USA", strip_attributes = TRUE)
L2241.GlobalTechCapFac_coal_vintage_USA <- get_data(all_data,"L2241.GlobalTechCapFac_coal_vintage_USA", strip_attributes = TRUE)
L2241.GlobalTechCapital_coal_vintage_USA <- get_data(all_data,"L2241.GlobalTechCapital_coal_vintage_USA", strip_attributes = TRUE)
L2241.GlobalTechEff_coal_vintage_USA <- get_data(all_data,"L2241.GlobalTechEff_coal_vintage_USA", strip_attributes = TRUE)
L2241.GlobalTechOMfixed_coal_vintage_USA <- get_data(all_data,"L2241.GlobalTechOMfixed_coal_vintage_USA", strip_attributes = TRUE)
L2241.GlobalTechOMvar_coal_vintage_USA <- get_data(all_data,"L2241.GlobalTechOMvar_coal_vintage_USA", strip_attributes = TRUE)
L2241.GlobalTechShrwt_coal_vintage_USA <- get_data(all_data,"L2241.GlobalTechShrwt_coal_vintage_USA", strip_attributes = TRUE)
L2241.StubTechEff_coal_vintage_USA <- get_data(all_data,"L2241.StubTechEff_coal_vintage_USA", strip_attributes = TRUE)
L2241.StubTechMarket_coal_vintage_USA <- get_data(all_data,"L2241.StubTechMarket_coal_vintage_USA", strip_attributes = TRUE)
L2241.StubTechProd_coal_vintage_USA <- get_data(all_data,"L2241.StubTechProd_coal_vintage_USA", strip_attributes = TRUE)
L2241.StubTechProfitShutdown_coal_vintage_USA <- get_data(all_data,"L2241.StubTechProfitShutdown_coal_vintage_USA", strip_attributes = TRUE)
L2241.StubTechSCurve_coal_vintage_USA <- get_data(all_data,"L2241.StubTechSCurve_coal_vintage_USA", strip_attributes = TRUE)
# ===================================================
# Define unique states and basins that have access to seawater that will
# allow for seawate cooling
seawater_states_basins <- unique(usa_seawater_states_basins$seawater_region)
# Process data
A23.elecS_tech_mapping_cool %>%
select(-supplysector, -water_type, -cooling_system, -plant_type) ->
A23.elecS_tech_mapping_cool
## Define several filtering and renaming fuctions that will be applied
## throughout the zchunk
# To account for new nesting-subsector structure and to add cooling technologies,
# we must expand certain outputs
add_cooling_techs <- function(data){
data %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("stub.technology" = "Electric.sector.technology",
"supplysector" = "Electric.sector","subsector")) %>%
select(-technology, -subsector_1)%>%
rename(technology = to.technology,
subsector0 = subsector,
subsector = stub.technology) -> data_new
data_new %>%
filter(grepl(gcamusa.WATER_TYPE_SEAWATER,technology),
(region %in% seawater_states_basins)) %>%
bind_rows(data_new %>%
filter(!grepl(gcamusa.WATER_TYPE_SEAWATER,technology))) %>%
arrange(region,year) -> data_new
return(data_new)
}
add_global_cooling_techs <- function(data){
data %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("technology" = "Electric.sector.technology",
"supplysector" = "Electric.sector",
"subsector")) %>%
select(-subsector_1, -technology.y) %>%
rename(sector.name = supplysector,
subsector.name0 = subsector,
subsector.name = technology,
technology = to.technology) %>%
mutate(technology = if_else(subsector.name0 == "wind" | subsector.name0 == "solar", subsector.name,
if_else(subsector.name0 == "grid_storage", subsector.name0, technology))) ->
data_new
return(data_new)
}
add_int_cooling_techs <- function(data){
data %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("supplysector" = "Electric.sector",
"intermittent.technology" = "Electric.sector.technology",
"subsector")) %>%
select(-technology, -subsector_1)%>%
rename(subsector0 = subsector,
subsector = intermittent.technology,
intermittent.technology = to.technology) ->
data_new
return(data_new)
}
# Here we will consolidate coal retire + coal vintages + other electricity subsectors that are
# currently located in separate files
# This also adds each cooling technology and trasfers coefficients calculated for cooling techs if needed
# All variables here are global
L2234.GlobalTechEff_elecS_USA %>%
bind_rows((L2241.GlobalTechEff_coal_vintage_USA %>%
rename(supplysector = sector.name,
subsector = subsector.name)),
L2241.GlobalTechEff_elec_coalret_USA) %>%
add_global_cooling_techs() %>%
select(-efficiency) %>%
# Bring in global cooling tech efficiencies from GCAM-core
left_join_keep_first_only(L2233.GlobalTechEff_elec_cool %>%
mutate(technology = gsub("_storage.*", "_base_storage", technology)) %>%
select(technology, efficiency,year),
by = c("technology", "year")) %>%
arrange(sector.name,year)->
L2233.GlobalTechEff_elec_cool_USA
L2234.GlobalTechShrwt_elecS_USA %>%
bind_rows(L2241.GlobalTechShrwt_coal_vintage_USA,
L2241.GlobalTechShrwt_elec_coalret_USA) %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("technology" = "Electric.sector.technology",
"sector.name" = "Electric.sector",
"subsector.name" = "subsector")) %>%
select(-subsector_1, -technology.y) %>%
rename(subsector.name0 = subsector.name, subsector.name = technology, technology = to.technology) %>%
mutate(technology = if_else(subsector.name0 == "wind" | subsector.name0 == "solar", subsector.name,
if_else(subsector.name0 == "grid_storage", subsector.name0, technology))) %>%
arrange(sector.name,year) ->
L2233.GlobalTechShrwt_elec_cool_USA
# Add all vintages to profit shutdown tibbles as they initially exist at state level, not global
L2234.GlobalTechProfitShutdown_elecS_USA %>%
bind_rows(L2241.GlobalTechProfitShutdown_elec_coalret_USA) %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("technology" = "Electric.sector.technology",
"supplysector" = "Electric.sector",
"subsector")) %>%
select(-subsector_1, -median.shutdown.point, -technology.y) %>%
rename(subsector0 = subsector, subsector = technology, technology = to.technology)%>%
left_join_keep_first_only(L2233.GlobalTechProfitShutdown_elec_cool %>%
## Keep_first_only is used to avoid unnessary
## multiplication of rows. We only want to bring
## in the global profit shutdowns for the technologies
## defined
select(technology, median.shutdown.point),
by=c("technology")) %>%
arrange(supplysector, year) %>%
mutate(technology = if_else(subsector0 == "wind" | subsector0 == "solar", subsector,
if_else(subsector0 == "grid_storage", subsector0, technology))) ->
L2233.GlobalTechProfitShutdown_elec_cool_USA
L2234.GlobalTechOMvar_elecS_USA %>%
bind_rows(L2241.GlobalTechOMvar_coal_vintage_USA %>%
rename(supplysector = sector.name,
subsector = subsector.name),
L2241.GlobalTechOMvar_elec_coalret_USA) %>%
add_global_cooling_techs() %>%
arrange(sector.name, year) ->
L2233.GlobalTechOMvar_elec_USA
L2234.GlobalTechOMfixed_elecS_USA %>%
bind_rows(L2241.GlobalTechOMfixed_coal_vintage_USA %>%
rename(supplysector = sector.name,
subsector = subsector.name),
L2241.GlobalTechOMfixed_elec_coalret_USA) %>%
add_global_cooling_techs() %>%
arrange(sector.name, year) ->
L2233.GlobalTechOMfixed_elec_USA
L2234.GlobalTechCapital_elecS_USA %>%
bind_rows(L2241.GlobalTechCapital_coal_vintage_USA %>%
rename(supplysector = sector.name,
subsector = subsector.name),
L2241.GlobalTechCapital_elec_coalret_USA) %>%
add_global_cooling_techs() %>%
arrange(sector.name, year) ->
L2233.GlobalTechCapital_elec_USA
L2233.GlobalTechCapital_elec_USA %>%
select(-input.capital, -capital.overnight, -fixed.charge.rate) %>%
left_join_keep_first_only(
## keep first only allows for capital costs to be pulled in the GCAM-core
## without unnecessary duplication caused by LJ. LJENM throws error.
bind_rows(L2233.GlobalTechCapital_elec_cool %>%
mutate(technology = gsub("storage", "base_storage", technology)),
L2233.GlobalTechCapital_elecPassthru %>%
mutate(technology=gsub("storage", "base_storage", technology))) %>%
select(technology, input.capital, capital.overnight, fixed.charge.rate),
by = c("technology")) %>%
arrange(sector.name,year) %>%
mutate(technology = if_else(subsector.name0 == "wind" | subsector.name0 == "solar", subsector.name,
if_else(subsector.name0 == "grid_storage", subsector.name0, technology))) %>%
na.omit()->
# remove battery options as they have no cooling options
L2233.GlobalTechCapital_elec_cool_USA
L2234.GlobalTechCapFac_elecS_USA %>%
bind_rows(L2241.GlobalTechCapFac_coal_vintage_USA %>%
rename(supplysector = sector.name,
subsector = subsector.name),
L2241.GlobalTechCapFac_elec_coalret_USA) %>%
add_global_cooling_techs() %>%
arrange(sector.name, year) ->
L2233.GlobalTechCapFac_elec_USA
# If there are not s-curves, specifically for coal, defined at the state level (L2233.StubTechSCurve_elec_USA below), we will
# we will assume that they follow the predefined lifetime and s-curves for all other techs
L2234.GlobalTechSCurve_elecS_USA %>%
add_global_cooling_techs() %>%
rename(supplysector = sector.name) %>%
arrange(supplysector, year) ->
L2233.GlobalTechSCurve_elecS_USA
# Assume that global tech coefficients map to all segments
L2233.GlobalTechCoef_elec_cool %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("subsector.name" = "technology",
"technology" = "to.technology")) %>%
select(-sector.name, -subsector_1, -subsector.name) %>%
na.omit() %>%
bind_rows(
L2233.GlobalTechCoef_elec_cool %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("subsector.name" = "technology")) %>%
filter(grepl("base_storage", to.technology)) %>%
select(-sector.name, -subsector_1, -subsector.name, -technology) %>%
rename(technology = to.technology) %>%
na.omit(),
L2233.GlobalTechCoef_elec_cool %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("technology")) %>%
filter(grepl("hydro", to.technology) | grepl("PV_base_storage", to.technology)) %>%
select(-sector.name, -subsector_1, -subsector.name, -technology) %>%
rename(technology = to.technology)) %>%
rename(supplysector = Electric.sector,
subsector0 = subsector,
subsector = Electric.sector.technology) %>%
right_join(L2233.GlobalTechEff_elec_cool_USA %>%
# Add all fuel, power plant, cooling tech, and all years
select(sector.name,subsector.name0,subsector.name,technology),
by = c("supplysector" = "sector.name",
"subsector0" = "subsector.name0",
"subsector" = "subsector.name",
"technology")) %>%
arrange(supplysector, subsector0, subsector, technology, year) %>%
na.omit() %>%
unique() ->
L2233.GlobalTechCoef_elecS_cool_USA
L2234.GlobalTechCapture_elecS_USA %>%
add_global_cooling_techs() %>%
rename(supplysector = sector.name) %>%
arrange(supplysector, year) ->
L2233.GlobalTechCapture_elecS_USA
# Coal vintage lifetimes are added at state level, therefore we remove all coal conv pul from the Global Lifetime values
L2234.GlobalTechLifetime_elecS_USA %>%
add_global_cooling_techs() %>%
rename(supplysector = sector.name) %>%
arrange(supplysector, year) ->
L2233.GlobalTechLifetime_elecS_cool_USA
L2234.AvgFossilEffKeyword_elecS_USA %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("technology" = "Electric.sector.technology",
"sector.name" = "Electric.sector",
"subsector.name" = "subsector")) %>%
select(-subsector_1, -technology.y) %>%
rename(subsector = technology,
technology = to.technology,
subsector.name0 = subsector.name) %>%
arrange(sector.name,year) ->
L2233.AvgFossilEffKeyword_elecS_USA
# Introduce GlobalInt techs
# We filter out all non-csp techs initially as these are these are the techs
# are the ones which need cooling techs added
csp_filter <- function(data){
data %>%
filter(!grepl("CSP", intermittent.technology)) %>%
rename(subsector0 = subsector,
subsector = intermittent.technology) %>%
mutate(intermittent.technology = subsector) ->
data_new
return(data_new)
}
# no changes needed for backup techs as cooling is not directly associated in previous cooling files
L2234.GlobalIntTechBackup_elecS_USA %>%
csp_filter() %>%
bind_rows(L2234.GlobalIntTechBackup_elecS_USA %>%
filter(grepl("CSP", intermittent.technology)) %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("supplysector" = "Electric.sector",
"intermittent.technology" = "Electric.sector.technology",
"subsector")) %>%
select(-technology, -subsector_1) %>%
rename(subsector0 = subsector,
subsector = intermittent.technology,
intermittent.technology = to.technology)) %>%
arrange(supplysector, subsector0, subsector, intermittent.technology, year)->
L2233.GlobalIntTechBackup_elecS_USA
# isolate int techs that do not have cooling techs associated
L2234.GlobalIntTechCapital_elecS_USA %>%
csp_filter() ->
L2233.GlobalIntTechCapital_elecS_USA
# Isolate CSP techs that have two capital costs
L2234.GlobalIntTechCapital_elecS_USA %>%
filter(grepl("CSP", intermittent.technology)) %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("intermittent.technology" = "Electric.sector.technology",
"supplysector" = "Electric.sector", "subsector")) %>%
select(-technology, -subsector_1) %>%
rename(subsector0 = subsector,
subsector = intermittent.technology,
intermittent.technology = to.technology) ->
L2233.GlobalIntTechCapital_elecS_cool_USA
L2233.GlobalIntTechCapital_elec_cool %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("subsector.name" = "subsector_1")) %>%
select(-sector.name, -subsector.name, -technology.x, -technology.y) %>%
rename(supplysector = Electric.sector,
subsector0 = subsector,
subsector = Electric.sector.technology,
intermittent.technology = to.technology) %>%
bind_rows(L2233.GlobalIntTechCapital_elecS_USA,
L2233.GlobalIntTechCapital_elecS_cool_USA) %>%
filter(!grepl("CSP_base", subsector)) %>%
# There are no additional cases of CSP_base across other Int Techs, therefore, we will remove
# as this has been introduced by calling gcam-core file L2233.GlobalIntTechCapital_elec_cool
arrange(supplysector, subsector0, subsector, intermittent.technology, year)->
L2233.GlobalIntTechCapital_elecS_cool_USA
# isolate CSP sectors which will need cooling tech layer added
L2234.GlobalIntTechEff_elecS_USA %>%
csp_filter()->
L2233.GlobalIntTechEff_elecS_USA
L2233.GlobalIntTechEff_elec_cool %>%
filter(grepl("CSP", technology)) %>%
mutate(technology = gsub("CSP", "CSP_storage", technology)) %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("subsector.name" = "subsector_1")) %>%
select(-sector.name, -subsector.name, -technology.y, -technology.x) %>%
filter((grepl("dry_hybrid", to.technology) & efficiency < 0.96)) %>%
# As we are not matching CSP names directly here, we want to make sure that the efficiency
# designated to dry_hybrid, 0.95, is the one that is adopted for all CSP (dry_hybrid) segments
bind_rows(L2233.GlobalIntTechEff_elec_cool %>%
filter(grepl("CSP", technology)) %>%
mutate(technology = gsub("CSP", "CSP_storage", technology)) %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("subsector.name" = "subsector_1")) %>%
select(-sector.name, -subsector.name, -technology.y, -technology.x) %>%
# As we are not matching CSP names directly here, we want to make sure that the efficiency
# designated to dry_hybrid, 0.95, is the one that is adopted for all CSP (dry_hybrid) segments
filter((grepl("recirculating", to.technology) & efficiency > 0.96))) %>%
rename(supplysector = Electric.sector,
subsector0 = subsector,
subsector = Electric.sector.technology,
intermittent.technology = to.technology) %>%
bind_rows(L2233.GlobalIntTechEff_elecS_USA) %>%
filter(subsector != "CSP_base") %>%
# There are no additional cases of CSP_base across other Int Techs, therefore, we will remove
# as this has been introduced by calling gcam-core file L2233.GlobalIntTechEff_elec_cool
arrange(supplysector, subsector0, subsector, intermittent.technology, year) ->
L2233.GlobalIntTechEff_elecS_cool_USA
# Add global water coefs from gcam-core to GCAM-USA. Maintain the global coefs
# Recommended to create state level water demand coefs in the future as state-level coefs are not currently applied
L2233.GlobalIntTechCoef_elec_cool %>%
# GCAM-core data has the subsector names for PV = solar, yet CSP = CSP, so we change the subsector
# name to allow for the mapping to be applied to PV as well
mutate(subsector.name = if_else(grepl("solar", subsector.name), technology, subsector.name)) %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by = c("subsector.name" = "subsector_1")) %>%
select(-sector.name, -subsector.name, -technology.y, -technology.x) %>%
rename(supplysector = Electric.sector,
subsector0 = subsector,
subsector = Electric.sector.technology,
intermittent.technology = to.technology) %>%
filter(!grepl("base_storage", subsector)) %>%
# PV and CSP base storage are not intermittent techs, therefore, we will remove
# as these have been introduced by calling gcam-core file L2233.GlobalIntTechEff_elec_cool
arrange(supplysector, subsector0, subsector, intermittent.technology, year) ->
L2233.GlobalIntTechCoef_elecS_cool_USA
L2234.GlobalIntTechLifetime_elecS_USA %>%
csp_filter() %>%
bind_rows(L2234.GlobalIntTechLifetime_elecS_USA %>%
filter(grepl("CSP", intermittent.technology)) %>%
add_int_cooling_techs) %>%
arrange(supplysector, subsector0, subsector, intermittent.technology, year) ->
L2233.GlobalIntTechLifetime_elecS_cool_USA
L2234.GlobalIntTechOMfixed_elecS_USA %>%
csp_filter() %>%
bind_rows(L2234.GlobalIntTechOMfixed_elecS_USA %>%
filter(grepl("CSP", intermittent.technology)) %>%
add_int_cooling_techs) %>%
arrange(supplysector, subsector0, subsector, intermittent.technology, year) ->
L2233.GlobalIntTechOMfixed_elecS_cool_USA
L2234.GlobalIntTechOMvar_elecS_USA %>%
mutate(subsector0 = subsector,
subsector = intermittent.technology) ->
L2233.GlobalIntTechOMvar_elecS_cool_USA
L2234.GlobalIntTechOMvar_elecS_USA %>%
mutate(subsector0 = subsector,
subsector = intermittent.technology) ->
L2233.GlobalIntTechOMvar_elecS_cool_USA
L2234.GlobalIntTechShrwt_elecS_USA %>%
filter(!grepl("CSP", intermittent.technology)) %>%
rename(subsector.name0 = subsector.name,
subsector.name = intermittent.technology) %>%
mutate(intermittent.technology = subsector.name) %>%
bind_rows(L2234.GlobalIntTechShrwt_elecS_USA %>%
filter(grepl("CSP", intermittent.technology)) %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("sector.name" = "Electric.sector",
"intermittent.technology" = "Electric.sector.technology",
"subsector.name" = "subsector")) %>%
select(-technology, -subsector_1) %>%
rename(subsector.name0 = subsector.name,
subsector.name = intermittent.technology,
intermittent.technology = to.technology)) %>%
arrange(sector.name, subsector.name0, subsector.name, intermittent.technology, year) ->
L2233.GlobalIntTechShrwt_elecS_cool_USA
L2234.PrimaryRenewKeyword_elecS_USA %>%
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
left_join(A23.elecS_tech_mapping_cool,
by=c("technology" = "Electric.sector.technology",
"sector.name" = "Electric.sector",
"subsector.name" = "subsector")) %>%
select(-subsector_1, -technology.y) %>%
rename(subsector = technology,
technology = to.technology,
subsector.name0 = subsector.name) %>%
arrange(sector.name, year) ->
L2233.PrimaryRenewKeyword_elecS_cool_USA
L2234.PrimaryRenewKeywordInt_elecS_USA %>%
filter(!grepl("CSP", intermittent.technology)) %>%
rename(subsector.name0 = subsector.name,
subsector.name = intermittent.technology) %>%
mutate(intermittent.technology = subsector.name) %>%
bind_rows(L2234.PrimaryRenewKeywordInt_elecS_USA %>%
filter(grepl("CSP", intermittent.technology)) %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("sector.name" = "Electric.sector",
"intermittent.technology" = "Electric.sector.technology",
"subsector.name" = "subsector")) %>%
select(-technology, -subsector_1) %>%
rename(subsector.name0 = subsector.name,
subsector.name = intermittent.technology,
intermittent.technology = to.technology)) %>%
arrange(sector.name, subsector.name0, subsector.name, intermittent.technology, year) ->
L2233.PrimaryRenewKeywordInt_elecS_cool_USA
# We can now look to state level data, once again combining vintages and adding cooling technologies
# Efficiencies do not change with the addition of cooling techs
L2234.StubTechEff_elecS_USA %>%
bind_rows(L2241.StubTechEff_coal_vintage_USA,
L2241.StubTechEff_elec_coalret_USA) %>%
add_cooling_techs() %>%
mutate(technology = if_else(subsector0 == "grid_storage", subsector0, technology)) ->
L2233.StubTechEff_elec_USA
L2234.StubTechMarket_elecS_USA %>%
bind_rows(L2241.StubTechMarket_coal_vintage_USA,
L2241.StubTechMarket_elec_coalret_USA) %>%
add_cooling_techs() %>%
mutate(technology = if_else(grepl("base_storage", subsector0), subsector0,
if_else(grepl("wind_base", subsector), subsector, technology))) ->
# temporary placement of base_storage cooling techs = nesting subsector
L2233.StubTechMarket_elec_USA
L1233.out_EJ_state_elec_F_tech_cool %>%
filter(year %in% MODEL_BASE_YEARS) %>%
left_join_error_no_match(elec_tech_water_map %>%
select(-from.supplysector, -from.subsector, -from.technology,
-minicam.energy.input, -sector, -to.subsector,-to.supplysector),
by = c("fuel", "technology", "cooling_system", "water_type")) %>%
select(-plant_type, -technology, -cooling_system, -water_type) %>%
rename(supplysector = sector, subsector0 = fuel, technology = to.technology, region = state) %>%
ungroup() ->
L1233.out_EJ_state_elec_F_tech_cool
# Combine elec segments, coal retire, and coal vintage calibrated production tables
L2234.StubTechProd_elecS_USA %>%
rename(tech.share.weight=share.weight) %>%
# use anti join to filter out entries in elec segments table which will be
# overwritten by coal retire technologies
anti_join(L2241.StubTechProd_elec_coalret_USA,
by = c("region", "supplysector", "subsector", "stub.technology", "year")) %>%
bind_rows(L2241.StubTechProd_elec_coalret_USA) %>%
# use anti join to filter out entries in table which will be overwritten
# by coal vintage technologies
anti_join(L2241.StubTechProd_coal_vintage_USA,
by = c("region", "supplysector", "subsector", "stub.technology", "year")) %>%
bind_rows(L2241.StubTechProd_coal_vintage_USA) %>%
add_cooling_techs() ->
L2233.StubTechProd_elec_USA
L2233.StubTechProd_elec_USA %>%
filter(calOutputValue > 0) %>%
left_join_keep_first_only(L1233.out_EJ_state_elec_F_tech_cool,
by = c("supplysector", "subsector0", "subsector", "technology", "region", "share.weight.year" = "year")) %>%
replace_na(list(share = 0)) %>%
group_by(supplysector, subsector0, subsector, region, year) %>%
# Divide by 2 to account for recirculating and dry_cooling technology types in CSP.
# These cooling shares are not included in L1233.out_EJ_state_elec_F_tech_cool.
mutate(calOutputValue = if_else(grepl("CSP", subsector), calOutputValue / 2,
# wind & pv don't have cooling techs and are assigned zero shares based on the replace_na above
# assign full calOutput value
if_else(subsector0 == "wind" | grepl("PV", subsector), calOutputValue, calOutputValue * share))) %>%
replace_na(list(calOutputValue = 0)) %>%
select(-value, -share) %>%
ungroup() %>%
unique() %>%
bind_rows(L2233.StubTechProd_elec_USA %>%
filter(calOutputValue == 0)) %>%
mutate(tech.share.weight = if_else(calOutputValue > 0, 1, 0)) %>%
group_by(supplysector, subsector0, subsector, region, year) %>%
mutate(subs.share.weight = if_else(sum(calOutputValue) > 0, 1, 0)) %>%
ungroup() %>%
arrange(region, supplysector, subsector0, year) ->
L2233.StubTechProd_elec_USA
# State level s-curves, combining vintages and initial slow and fast retire plants
bind_rows(L2241.StubTechSCurve_coal_vintage_USA,
L2241.StubTechSCurve_elec_coalret_USA) %>%
add_cooling_techs() ->
L2233.StubTechSCurve_elec_USA
L2241.StubTechProfitShutdown_coal_vintage_USA %>%
add_cooling_techs() ->
L2233.StubTechProfitShutdown_elecS_cool_USA
L2234.StubTechCapFactor_elecS_solar_USA %>%
add_cooling_techs() ->
L2233.StubTechCapFactor_elecS_solar_USA
L2234.StubTechCapFactor_elecS_wind_USA %>%
add_cooling_techs() %>%
mutate(technology = if_else(grepl("wind_base", subsector), subsector, technology)) ->
L2233.StubTechCapFactor_elecS_wind_USA
L2234.StubTechElecMarket_backup_elecS_USA %>%
add_cooling_techs() %>%
mutate(technology = if_else(subsector == "rooftop_pv" | grepl("wind_base", subsector), subsector, technology)) ->
L2233.StubTechElecMarket_backup_elecS_USA
L2234.StubTechFixOut_elecS_USA %>%
add_cooling_techs() ->
L2233.StubTechFixOut_elecS_USA
L2234.StubTechFixOut_hydro_elecS_USA %>%
add_cooling_techs() ->
L2233.StubTechFixOut_hydro_elecS_USA
L2234.StubTechMarket_backup_elecS_USA %>%
add_cooling_techs() %>%
mutate(technology = if_else(subsector == "rooftop_pv" | grepl("wind_base", subsector), subsector, technology)) ->
L2233.StubTechMarket_backup_elecS_USA
L2234.StubTechCost_offshore_wind_elecS_USA %>%
add_cooling_techs() ->
L2233.StubTechCost_offshore_wind_elecS_USA
L2234.SubsectorLogit_elecS_USA %>%
rename(subsector0 = subsector) %>%
mutate(subsector.1 = subsector0) %>%
select(-subsector.1) %>%
arrange(supplysector) ->
L2233.SubsectorLogit_elecS_USA
# Create logit table at subsector level by including all possible fule types (i.e. hydro, battery, etc.)
L2234.SubsectorLogit_elecS_USA %>%
left_join(A23.elecS_tech_mapping_cool,
# Left_join used as each power plant type will now be multiplied
# by up to five cooling technologies, thus increasing tibble size
by = c("supplysector" = "Electric.sector", "subsector")) %>%
rename(subsector0 = subsector,
subsector = Electric.sector.technology) %>%
right_join(bind_rows(L2233.StubTechMarket_elec_USA %>%
select(subsector, region, technology),
L2233.StubTechFixOut_hydro_elecS_USA %>%
select(subsector, region, technology),
L2233.StubTechEff_elec_USA %>%
filter(subsector == "battery") %>%
select(subsector, region, technology)),
# Including all possible technologies here
by = c("subsector", "region", "to.technology" = "technology")) %>%
select(region, supplysector, subsector0, subsector, logit.year.fillout, logit.exponent,logit.type) %>%
# Acknowledge that not all vintages are in each state, therefore shareweights and logits are
# not needed for these vintages
unique() %>%
arrange(supplysector) ->
L2233.SubsectorLogit_elecS_cool_USA
L2233.SubsectorLogit_elecS_cool_USA %>%
select(region, supplysector, subsector0, subsector) %>%
# select which load segment fuel + power plant exist in each state
left_join(L2233.GlobalTechCoef_elecS_cool_USA,
## LJ used as coefficients are added for all historical years for only the
## load segement, fuel, and power plants that exist. This increases data set size,
## requiring LJ.
by = c("supplysector", "subsector0", "subsector")) %>%
mutate(market.name = if_else(minicam.energy.input == gcamusa.WATER_TYPE_SEAWATER, gcam.USA_REGION, region)) %>%
na.omit() ->
L2233.StubTechCoef_elecS_cool_USA
L2233.StubTechCoef_elecS_cool_USA %>%
filter(grepl(gcamusa.WATER_TYPE_SEAWATER, technology),
(region %in% seawater_states_basins)) %>%
bind_rows(L2233.StubTechCoef_elecS_cool_USA %>%
filter(!grepl(gcamusa.WATER_TYPE_SEAWATER, technology))) %>%
arrange(region, year) ->
# Not all techs have cooling options, therefore we remove these
L2233.StubTechCoef_elecS_cool_USA
L2234.SubsectorShrwt_elecS_USA %>%
rename(subsector0 = subsector) %>%
bind_rows(
L2234.StubTechProd_elecS_USA %>%
select(region, supplysector, subsector, year, subs.share.weight) %>%
rename(share.weight = subs.share.weight, subsector0 = subsector) %>%
unique(),
L2234.StubTechFixOut_elecS_USA %>%
select(region, supplysector, subsector, year, subs.share.weight) %>%
rename(share.weight = subs.share.weight,
subsector0 = subsector) %>%
unique()
) %>%
arrange(region, supplysector, year) ->
L2233.SubsectorShrwt_elecS_USA
L2234.SubsectorShrwtInterp_elecS_USA %>%
rename(subsector0 = subsector) %>%
mutate(subsector.1 = subsector0) %>%
select(-subsector.1) %>%
arrange(supplysector) ->
L2233.SubsectorShrwtInterp_elecS_USA
L2234.SubsectorShrwtInterpTo_elecS_USA %>%
rename(subsector0 = subsector) %>%
mutate(subsector.1 = subsector0) %>%
select(-subsector.1) %>%
arrange(supplysector) ->
L2233.SubsectorShrwtInterpTo_elecS_USA
# Subsector shareweights are really generation technology shareweights
# These use the global tech object in L2234, so copy to all regions
# No interpolation function is needed
L2233.StubTechProd_elec_USA %>%
# calculate historical subsector (generation technology) shareweights
group_by(region, supplysector, subsector0, subsector, year) %>%
summarise(calOutputValue = sum(calOutputValue)) %>%
ungroup() %>%
# if no historical production, assign 0 shareweight; otherwise, assign 1 shareweight
mutate(share.weight = if_else(calOutputValue > 0, 1, 0)) %>%
select(-calOutputValue) ->
L2233.SubsectorShrwt_elecS_cool_USA_hist
L2234.GlobalTechShrwt_elecS_USA %>%
bind_rows(L2234.GlobalIntTechShrwt_elecS_USA %>%
rename(technology = intermittent.technology),
L2241.GlobalTechShrwt_elec_coalret_USA,
L2241.GlobalTechShrwt_coal_vintage_USA) %>%
repeat_add_columns(tibble::tibble(region = gcamusa.STATES)) %>%
rename(supplysector = sector.name,
subsector0 = subsector.name,
subsector = technology) %>%
# we only want future years here, because past years are dictated by state-level production
filter(year %in% MODEL_FUTURE_YEARS) %>%
# semi_join historical table to filter out techs that shouldn't be created,
# such as CSP and geothermal in regions without this resource
semi_join(L2233.SubsectorShrwt_elecS_cool_USA_hist,
by = c("region", "supplysector", "subsector0", "subsector")) %>%
select(region, supplysector, subsector0, subsector, year, share.weight) ->
L2233.SubsectorShrwt_elecS_cool_USA_fut
L2233.SubsectorShrwt_elecS_cool_USA_hist %>%
bind_rows(L2233.SubsectorShrwt_elecS_cool_USA_fut) %>%
arrange(region,supplysector,year) ->
L2233.SubsectorShrwt_elecS_cool_USA
# Prepare interpolation rules for all power plant + cooling system combinations
# First, we assume that if the generation technology exists in the historical period
# and is allowed to continue into future periods, the cooling technology shares will
# be held constant into the future. The exception is once through cooling, whose
# share weights will be 0 from 2020-2100 to mirror GCAM-core.
L2233.StubTechProd_elec_USA %>%
filter(year == max(MODEL_BASE_YEARS)) %>%
# join in subsector shareweights so we know which generation technologies
# are allowed to deploy in the future
left_join_error_no_match(L2233.SubsectorShrwt_elecS_cool_USA %>%
filter(year %in% (MODEL_FUTURE_YEARS)) %>%
group_by(region, supplysector, subsector0, subsector) %>%
# check if a generation tech has non-zero share-weight in any future period (i.e. sum > 0)
summarise(future.subs.shrwt = if_else(sum(share.weight) > 0, 1, 0)) %>%
ungroup(),
by = c("region", "supplysector", "subsector0", "subsector")) -> L2233.StubTechProd_elec_cool_SW_USA
# Set all once through technologies to zero in all future periods.
L2233.StubTechProd_elec_cool_SW_USA %>%
filter(grepl(gcamusa.DISALLOWED_COOLING_TECH, technology)) %>%
mutate(from.year = min(MODEL_FUTURE_YEARS),
to.year = max(MODEL_YEARS),
interpolation.function = gcamusa.FIXED_SHAREWEIGHT,
to.value = 0) %>%
rename(stub.technology = technology) %>%
mutate(apply.to = gcamusa.INTERP_APPLY_TO) %>%
select(region, supplysector, subsector0, subsector, stub.technology, apply.to,
from.year, to.year, to.value, interpolation.function) -> L2233.StubTechInterpTo_elecS_oncethrough_USA
# If the particular load segment / generation technology produced historically,
# fix technology (cooling system) share weights to calibration values
# for all future periods. We do this even if the particular load segment /
# generation technology is not allowed to deploy in the future - these assumptions
# are handled at the subsector (generation technology) level.
L2233.StubTechProd_elec_cool_SW_USA %>%
filter(!grepl(gcamusa.DISALLOWED_COOLING_TECH, technology),
subs.share.weight > 0 & future.subs.shrwt > 0) %>%
mutate(from.year = max(MODEL_BASE_YEARS),
to.year = max(MODEL_YEARS),
interpolation.function = gcamusa.FIXED_SHAREWEIGHT) %>%
rename(stub.technology = technology) %>%
mutate(apply.to = gcamusa.INTERP_APPLY_TO) %>%
select(region, supplysector, subsector0, subsector, stub.technology, apply.to,
from.year, to.year, interpolation.function) -> L2233.StubTechInterp_elecS_cool_USA
# Second, if a generation technology did not exist in the historical period (i.e. CSP, IGCC, etc.),
# but exists in the future, then the share weights for all non-once through cooling technologies
# will be set to 1.
# NOTE: In a very few instances, this includes generation technologies which produced historically
# but not in the given load segment in question. In these cases, we still set future share weights
# for all cooling techs to 1 in future periods, even though they may have deployed to different
# extents in the load segment where the generation technology did produce histroically.
L2233.StubTechProd_elec_cool_SW_USA %>%
filter(!grepl(gcamusa.DISALLOWED_COOLING_TECH, technology),
subs.share.weight == 0 & future.subs.shrwt > 0) %>%
mutate(from.year = min(MODEL_FUTURE_YEARS),
to.year = max(MODEL_YEARS),
interpolation.function = gcamusa.FIXED_SHAREWEIGHT,
to.value = gcamusa.DEFAULT_SHAREWEIGHT) %>%
rename(stub.technology = technology) %>%
mutate(apply.to = gcamusa.INTERP_APPLY_TO) %>%
select(region, supplysector, subsector0, subsector, stub.technology, apply.to,
from.year, to.year, to.value, interpolation.function) -> L2233.StubTechInterpTo_elecS_fut_USA
# Third, if a fuel and power plant combination did exist in the historical period,
# but switches to a new power plant type (i.e. Nuclear Gen 2 -> Gen 3), we assume
# that share weights of cooling technologies for that particular state remain similar
# to the old power plant (e.g. Gen 3 will have the same cooling tech share weights as Gen 2).
# Create a table with future techs whose cooling shares we can infer from existing ones
L2233.StubTechProd_elec_cool_SW_USA %>%
filter(!grepl(gcamusa.DISALLOWED_COOLING_TECH, technology),
subs.share.weight == 0 & future.subs.shrwt > 0) %>%
# Get rid of info related to calibrated values, which we've just confirmed are zero
select(-calOutputValue, -share.weight.year, -subs.share.weight, -tech.share.weight) %>%
# use semi_join to filter for future generation technologies which are mapped to current gen techs
semi_join(A23.elecS_tech_mapping_cool_shares_fut,
by = "subsector") %>%
left_join_error_no_match(A23.elecS_tech_mapping_cool_shares_fut,
by = "subsector") %>%
left_join_error_no_match(elec_tech_water_map %>%
select(to.technology, cooling_system),
by = c("technology" = "to.technology")) -> L2233.elec_cool_SW_future_techs_USA
# Create a table with existing techs whose cooling shares we can use to inform future ones
L2233.StubTechProd_elec_cool_SW_USA %>%
filter(!grepl(gcamusa.DISALLOWED_COOLING_TECH, technology)) %>%
# use semi_join to filter for current generation technologies which are used to inform
# future gen tech cooling shares
semi_join(A23.elecS_tech_mapping_cool_shares_fut,
by = c("subsector" = "mapped_subsector")) %>%
left_join_error_no_match(elec_tech_water_map %>%
select(to.technology, cooling_system),
by = c("technology" = "to.technology")) -> L2233.elec_cool_SW_mapped_techs_USA
# Join tables and match up share info
L2233.elec_cool_SW_future_techs_USA %>%
left_join_error_no_match(L2233.elec_cool_SW_mapped_techs_USA %>%
select(-technology, -future.subs.shrwt),
by = c("region", "supplysector", "subsector0", "year",
"mapped_subsector" = "subsector", "cooling_system")) %>%
group_by(region, supplysector, subsector0, subsector) %>%
# check if a generation tech has non-zero share-weight in any future period (i.e. sum > 0)
mutate(subs.share.weight = if_else(sum(calOutputValue) > 0, 1, 0)) %>%
# Remove any generation techs with zero generation by mapped technologies,
# which will result in zero shares for every cooling tech.
# This could happen if once through had 100% share historically, since
# once through is not included in this (future-oriented) table.
filter(subs.share.weight != 0) %>%
# calculate new cooling tech shares (share weights) without once through
mutate(share.weight = round(calOutputValue / sum(calOutputValue), energy.DIGITS_SHRWT)) %>%
ungroup() %>%
mutate(from.year = min(MODEL_FUTURE_YEARS),
to.year = max(MODEL_YEARS),
interpolation.function = gcamusa.FIXED_SHAREWEIGHT,
to.value = share.weight,
apply.to = gcamusa.INTERP_APPLY_TO) %>%
rename(stub.technology = technology) %>%
select(region, supplysector, subsector0, subsector, stub.technology, apply.to,
from.year, to.year, to.value, interpolation.function) -> L2233.StubTechInterpTo_elecS_mapped_USA
# Finally, all power plant and cooling technology combinations that do not exist in
# in future years are given 0 share weights in the future periods.
L2233.StubTechProd_elec_cool_SW_USA %>%
filter(future.subs.shrwt == 0) %>%
mutate(from.year = min(MODEL_FUTURE_YEARS),
to.year = max(MODEL_YEARS),
interpolation.function = gcamusa.FIXED_SHAREWEIGHT,
to.value = 0) %>%
rename(stub.technology = technology) %>%
mutate(apply.to = gcamusa.INTERP_APPLY_TO) %>%
select(region, supplysector, subsector0, subsector, stub.technology, apply.to,
from.year, to.year, to.value, interpolation.function) ->
L2233.StubTechInterpTo_elecS_nofut_USA
# Combine all "InterpTo" cases which specify a particular future shareweight value
L2233.StubTechInterpTo_elecS_oncethrough_USA %>%
bind_rows(L2233.StubTechInterpTo_elecS_fut_USA,
L2233.StubTechInterpTo_elecS_nofut_USA) %>%
# use anti-join to avoid duplicates, since the scope of L2233.StubTechInterpTo_elecS_mapped_USA
# overlaps with that of L2233.StubTechInterpTo_elecS_nofut_USA
anti_join(L2233.StubTechInterpTo_elecS_mapped_USA,
by = c("region", "supplysector", "subsector0", "subsector", "stub.technology")) %>%
bind_rows(L2233.StubTechInterpTo_elecS_mapped_USA) %>%
# use anti-join to remove any technologies which are fixed at calibration values
anti_join(L2233.StubTechInterp_elecS_cool_USA,
by = c("region", "supplysector", "subsector0", "subsector", "stub.technology")) ->
L2233.StubTechInterpTo_elecS_cool_USA
# Make a table with shareweights for start and end points of "InterpTo" rules
L2233.StubTechInterpTo_elecS_cool_USA %>%
gather(drop, year, from.year, to.year) %>%
select(region, supplysector, subsector0, subsector, stub.technology, year, share.weight = to.value) ->
L2233.StubTechShrwt_elecS_cool_USA
# Combine all interpolation cases
L2233.StubTechInterp_elecS_cool_USA %>%
bind_rows(L2233.StubTechInterpTo_elecS_cool_USA %>%
# get rid of to.value to consolidate to one table
# to.value is now reflected in L2233.StubTechShrwt_elecS_cool_USA
select(-to.value)) -> L2233.StubTechInterp_elecS_cool_USA
# Only done to manipulate variable and not throw an error
L2234.Supplysector_elecS_USA %>%
mutate(supplysector.1 = supplysector) %>%
select(-supplysector.1) ->
L2233.Supplysector_elecS_USA
# ===================================================
# Produce outputs
L2233.GlobalTechEff_elec_cool_USA %>%
add_title("Electricity Load Segments Technology Efficiencies") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Efficiencies") %>%
add_legacy_name("L2233.GlobalTechEff_elec_cool") %>%
add_precursors("L2234.GlobalTechEff_elecS_USA",
"L2241.GlobalTechEff_coal_vintage_USA",
"L2241.GlobalTechEff_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool",
"L2233.GlobalTechEff_elec_cool") ->
L2233.GlobalTechEff_elecS_cool_USA
L2233.GlobalTechShrwt_elec_cool_USA %>%
add_title("Electricity Load Segments Technology Shareweights") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Shareweights") %>%
add_legacy_name("L2233.GlobalTechShrwt_elec_cool") %>%
add_precursors("L2234.GlobalTechShrwt_elecS_USA",
"L2241.GlobalTechShrwt_coal_vintage_USA",
"L2241.GlobalTechShrwt_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool",
"L2233.GlobalTechShrwt_elec_cool") ->
L2233.GlobalTechShrwt_elecS_cool_USA
L2233.GlobalTechProfitShutdown_elec_cool_USA %>%
add_title("Electricity Load Segments Technology Profit Shutdown Decider") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Profit Shutdown Decider") %>%
add_legacy_name("L2233.GlobalTechProfitShutdown_elec_cool") %>%
add_precursors("L2234.GlobalTechProfitShutdown_elecS_USA",
"L2241.GlobalTechProfitShutdown_elec_coalret_USA",
"L2241.StubTechProfitShutdown_coal_vintage_USA",
"gcam-usa/A23.elecS_tech_mapping_cool",
"L2233.GlobalTechProfitShutdown_elec_cool") ->
L2233.GlobalTechProfitShutdown_elecS_cool_USA
L2233.GlobalTechOMvar_elec_USA %>%
add_title("Electricity Load Segments Technology Variable OM Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Variable OM Costs") %>%
add_legacy_name("L2233.GlobalTechOMvar_elec") %>%
add_precursors("L2234.GlobalTechOMvar_elecS_USA",
"L2241.GlobalTechOMvar_coal_vintage_USA",
"L2241.GlobalTechOMvar_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalTechOMvar_elecS_cool_USA
L2233.GlobalTechOMfixed_elec_USA %>%
add_title("Electricity Load Segments Technology Fixed OM Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Fixed OM Costs") %>%
add_legacy_name("L2233.GlobalTechOMfixed_elec") %>%
add_precursors("L2234.GlobalTechOMfixed_elecS_USA",
"L2241.GlobalTechOMfixed_coal_vintage_USA",
"L2241.GlobalTechOMfixed_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalTechOMfixed_elecS_cool_USA
L2233.GlobalTechCapital_elec_USA %>%
add_title("Electricity Load Segments Technology Capital Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Capital Costs") %>%
add_legacy_name("L2233.GlobalTechCapital_elec") %>%
add_precursors("L2234.GlobalTechCapital_elecS_USA",
"L2241.GlobalTechCapital_coal_vintage_USA",
"L2241.GlobalTechCapital_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalTechCapital_elecS_USA
L2233.GlobalTechCapital_elec_cool_USA %>%
add_title("Electricity Load Segments Technology Capital Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology Capital Costs") %>%
add_legacy_name("L2233.GlobalTechCapital_elec_cool") %>%
add_precursors("L2234.GlobalTechCapital_elecS_USA",
"L2241.GlobalTechCapital_coal_vintage_USA",
"L2241.GlobalTechCapital_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool",
"L2233.GlobalTechCapital_elec_cool",
"L2233.GlobalTechCapital_elecPassthru") ->
L2233.GlobalTechCapital_elecS_cool_USA
L2233.GlobalTechCapFac_elec_USA %>%
add_title("Global Capacity Factors for Electricity Load Segments Technologies") %>%
add_units("none") %>%
add_comments("Global Capacity Factors for Electricity Load Segments Technologies") %>%
add_legacy_name("L2233.GlobalTechCapFac_elec") %>%
add_precursors("L2234.GlobalTechCapFac_elecS_USA",
"L2241.GlobalTechCapFac_coal_vintage_USA",
"L2241.GlobalTechCapFac_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalTechCapFac_elecS_cool_USA
L2233.GlobalTechSCurve_elecS_USA %>%
add_title("Electricity Load Segments Technology S-curve Shutdown Decider") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Technology S-curve Shutdown Decider") %>%
add_legacy_name("L2233.GlobalTechSCurve_elec") %>%
add_precursors("L2234.GlobalTechSCurve_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalTechSCurve_elecS_cool_USA
L2233.GlobalTechCoef_elecS_cool_USA %>%
add_title("Weighted water coefficients for reference scenario and load segment classification") %>%
add_units("none") %>%
add_comments("Weighted water coefficients for reference scenario and load segment classification") %>%
add_legacy_name("L2233.GlobalTechCoef_elec_cool") %>%
add_precursors("L2233.GlobalTechCoef_elec_cool",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalTechCoef_elecS_cool_USA
L2233.GlobalTechCapture_elecS_USA %>%
add_title("Electricity Load Segments CCS Technology Characteristics") %>%
add_units("none") %>%
add_comments("Electricity Load Segments CCS Technology Characteristics") %>%
add_legacy_name("L2233.GlobalTechCapture_elec") %>%
add_precursors("L2234.GlobalTechCapture_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool")->
L2233.GlobalTechCapture_elecS_cool_USA
L2233.GlobalTechLifetime_elecS_cool_USA %>%
add_title("Electricity Load Segments Lifetime") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Lifetime") %>%
add_legacy_name("L2233.GlobalTechLifetime_elec_cool") %>%
add_precursors("L2234.GlobalTechLifetime_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool")->
L2233.GlobalTechLifetime_elecS_cool_USA
L2233.AvgFossilEffKeyword_elecS_USA %>%
add_title("Average Fossil Efficiency Keywords for Electricity Load Segments Technologies") %>%
add_units("none") %>%
add_comments("Average Fossil Efficiency Keywords for Electricity Load Segments Technologies") %>%
add_legacy_name("L2233.AvgFossilEffKeyword_elec") %>%
add_precursors("L2234.AvgFossilEffKeyword_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.AvgFossilEffKeyword_elecS_cool_USA
L2233.GlobalIntTechBackup_elecS_USA %>%
add_title("Electricity Load Segments Intermittent Technology Backup Characteristics") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Backup Characteristics") %>%
add_legacy_name("L2233.GlobalIntTechBackup_elec") %>%
add_precursors("L2234.GlobalIntTechBackup_elecS_USA") ->
L2233.GlobalIntTechBackup_elecS_cool_USA
L2233.GlobalIntTechCapital_elecS_USA %>%
add_title("Electricity Load Segments Intermittent Technology Capital Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Capital Costs") %>%
add_legacy_name("L2233.GlobalIntTechCapital_elec") %>%
add_precursors("L2234.GlobalIntTechCapital_elecS_USA") ->
L2233.GlobalIntTechCapital_elecS_USA
L2233.GlobalIntTechCapital_elecS_cool_USA %>%
add_title("Electricity Load Segments Intermittent Technology Capital Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Capital Costs") %>%
add_legacy_name(" L2233.GlobalIntTechCapital_elec_cool") %>%
add_precursors("L2234.GlobalIntTechCapital_elecS_USA",
"L2233.GlobalIntTechCapital_elec_cool",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalIntTechCapital_elecS_cool_USA
L2233.GlobalIntTechEff_elecS_USA %>%
add_title("Electricity Load Segments Intermittent Technology Efficiencies") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Efficiencies") %>%
add_legacy_name("L2233.GlobalIntTechEff_elec") %>%
add_precursors("L2234.GlobalIntTechEff_elecS_USA") ->
L2233.GlobalIntTechEff_elecS_USA
L2233.GlobalIntTechEff_elecS_cool_USA %>%
add_title("Electricity Load Segments Intermittent Technology Efficiencies") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Efficiencies") %>%
add_legacy_name("L2233.GlobalIntTechEff_elec") %>%
add_precursors("L2234.GlobalIntTechEff_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool",
"L2233.GlobalIntTechEff_elec_cool") ->
L2233.GlobalIntTechEff_elecS_cool_USA
L2233.GlobalIntTechLifetime_elecS_cool_USA %>%
add_title("Electricity Load Segments Intermittent Technology Lifetimes") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Lifetimes") %>%
add_legacy_name("L2233.GlobalIntTechLifetime_elec_cool") %>%
add_precursors("L2234.GlobalIntTechLifetime_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalIntTechLifetime_elecS_cool_USA
L2233.GlobalIntTechOMfixed_elecS_cool_USA %>%
add_title("Electricity Load Segments Intermittent Technology Fixed OM Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Fixed OM Costs") %>%
add_legacy_name("L2233.GlobalIntTechOMfixed_elec_cool") %>%
add_precursors("L2234.GlobalIntTechOMfixed_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalIntTechOMfixed_elecS_cool_USA
L2233.GlobalIntTechOMvar_elecS_cool_USA %>%
add_title("Electricity Load Segments Intermittent Technology Variable OM Costs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Variable OM Costs") %>%
add_legacy_name("L2233.GlobalIntTechOMvar_elec_cool") %>%
add_precursors("L2234.GlobalIntTechOMvar_elecS_USA") ->
L2233.GlobalIntTechOMvar_elecS_cool_USA
L2233.GlobalIntTechShrwt_elecS_cool_USA %>%
add_title("Electricity Load Segments Intermittent Technology Shareweights") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Intermittent Technology Shareweights") %>%
add_legacy_name("L2233.GlobalIntTechShrwt_elec_cool") %>%
add_precursors("L2234.GlobalIntTechShrwt_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalIntTechShrwt_elecS_cool_USA
L2233.GlobalIntTechCoef_elecS_cool_USA %>%
add_title("Water demand coefs for int techs") %>%
add_units("none") %>%
add_comments("Water demand coefs for int techs") %>%
add_legacy_name("L2233.GlobalIntTechCoef_elec_cool") %>%
add_precursors("L2233.GlobalIntTechCoef_elec_cool",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.GlobalIntTechCoef_elecS_cool_USA
L2233.PrimaryRenewKeyword_elecS_cool_USA %>%
add_title("Primary Renewable Keywords for Electricity Load Segments Technologies") %>%
add_units("none") %>%
add_comments("Primary Renewable Keywords for Electricity Load Segments Technologies") %>%
add_legacy_name("L2233.PrimaryRenewKeyword_elec_cool") %>%
add_precursors("L2234.PrimaryRenewKeyword_elecS_USA") ->
L2233.PrimaryRenewKeyword_elecS_cool_USA
L2233.PrimaryRenewKeywordInt_elecS_cool_USA %>%
add_title("Primary Renewable Keywords for Electricity Load Segments Intermittent Technologies") %>%
add_units("none") %>%
add_comments("Primary Renewable Keywords for Electricity Load Segments Intermittent Technologies") %>%
add_legacy_name("L2233.PrimaryRenewKeywordInt_elec_cool") %>%
add_precursors("L2234.PrimaryRenewKeywordInt_elecS_USA") ->
L2233.PrimaryRenewKeywordInt_elecS_cool_USA
L2233.StubTechEff_elec_USA %>%
add_title("Electricity Load Segments Base Year Efficiencies") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Base Year Efficiencies") %>%
add_legacy_name("L2233.StubTechEff_elec") %>%
add_precursors("L2234.StubTechEff_elecS_USA",
"L2241.StubTechEff_coal_vintage_USA",
"L2241.StubTechEff_elec_coalret_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechEff_elecS_cool_USA
L2233.StubTechCoef_elecS_cool_USA %>%
add_title("Water demand coefficients at state level for Electricity Load Segments") %>%
add_units("none") %>%
add_comments("Water demand coefficients at state level for Electricity Load Segments") %>%
add_legacy_name("L2233.StubTechCoef_elec") %>%
add_precursors("L2233.GlobalTechCoef_elec_cool",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechCoef_elecS_cool_USA
L2233.StubTechMarket_elec_USA %>%
add_title("Energy Inputs for Electricity Load Segments and associated Cooling Technologies") %>%
add_units("none") %>%
add_comments("Energy Inputs for Electricity Load Segments and associated Cooling Technologies") %>%
add_legacy_name("L2233.StubTechMarket_elec") %>%
add_precursors("L2234.StubTechMarket_elecS_USA",
"L2241.StubTechMarket_coal_vintage_USA",
"L2241.StubTechMarket_elec_coalret_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechMarket_elecS_cool_USA
L2233.StubTechProd_elec_USA %>%
add_title("Electricity Load Segments and Cooling Technology Calibration Outputs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments and Cooling Technology Calibration Outputs") %>%
add_legacy_name("L2233.StubTechProd_elec") %>%
add_precursors("L2234.StubTechProd_elecS_USA",
"L2241.StubTechProd_coal_vintage_USA",
"L2241.StubTechProd_elec_coalret_USA",
"gcam-usa/A23.elecS_tech_mapping_cool",
"L1233.out_EJ_state_elec_F_tech_cool",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/elec_tech_water_map") ->
L2233.StubTechProd_elecS_cool_USA
L2233.StubTechSCurve_elec_USA %>%
add_title("Electricity Load Segment and Cooling Technology S-Curves") %>%
add_units("none") %>%
add_comments("Electricity Load Segment and Cooling Technology S-Curves") %>%
add_legacy_name("L2233.StubTechSCurve_elec") %>%
add_precursors("L2241.StubTechSCurve_coal_vintage_USA",
"L2241.StubTechSCurve_elec_coalret_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechSCurve_elecS_cool_USA
L2233.StubTechProfitShutdown_elecS_cool_USA %>%
add_title("Electricity Load Segment and Cooling Technology Profit Shutdown Decider") %>%
add_units("none") %>%
add_comments("Electricity Load Segment and Cooling Technology Profit Shutdown Decider") %>%
add_legacy_name("L2233.StubTechSCurve_elec") %>%
add_precursors("L2241.StubTechProfitShutdown_coal_vintage_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechProfitShutdown_elecS_cool_USA
L2233.StubTechCapFactor_elecS_solar_USA %>%
add_title("State-specific Capacity Factors for Electricity Load Segments Solar and Cooling Technologies") %>%
add_units("none") %>%
add_comments("State-specific Capacity Factors for Electricity Load Segments Solar and Cooling Technologies") %>%
add_legacy_name("L2233.StubTechCapFactor_elec_solar") %>%
add_precursors("L2234.StubTechCapFactor_elecS_solar_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechCapFactor_elecS_solar_USA
L2233.StubTechCapFactor_elecS_wind_USA %>%
add_title("State-specific Capacity Factors for Electricity Load Segments Wind Technologies") %>%
add_units("none") %>%
add_comments("State-specific Capacity Factors for Electricity Load Segments Wind Technologies") %>%
add_legacy_name("L2233.StubTechCapFactor_elec_wind") %>%
add_precursors("L2234.StubTechCapFactor_elecS_wind_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechCapFactor_elecS_wind_USA
L2233.StubTechElecMarket_backup_elecS_USA %>%
add_title("Electricity Load Segments Sector Name for Backup Markets") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Sector Name for Backup Markets") %>%
add_legacy_name("L2233.StubTechElecMarket_backup_elec") %>%
add_precursors("L2234.StubTechElecMarket_backup_elecS_USA",
"gcam-usa/usa_seawater_states_basins",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechElecMarket_backup_elecS_cool_USA
L2233.StubTechFixOut_elecS_USA %>%
add_title("Electricity Load Segments Fixed Outputs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Fixed Outputs") %>%
add_legacy_name("L2233.StubTechFixOut_elec") %>%
add_precursors("L2234.StubTechFixOut_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechFixOut_elecS_cool_USA
L2233.StubTechFixOut_hydro_elecS_USA %>%
add_title("Electricity Load Segments Hydro Fixed Outputs") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Hydro Fixed Outputs") %>%
add_legacy_name("L2233.StubTechFixOut_hydro_elec") %>%
add_precursors("L2234.StubTechFixOut_hydro_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechFixOut_hydro_elecS_cool_USA
L2233.StubTechCost_offshore_wind_elecS_USA %>%
add_title("Electricity Load Segments Offshore Wind Cost Adjustment") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Offshore Wind Cost Adjustment") %>%
add_legacy_name("L2233.StubTechCost_offshore_wind_elec_USA") %>%
add_precursors("L2234.StubTechCost_offshore_wind_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechCost_offshore_wind_elecS_cool_USA
L2233.StubTechMarket_backup_elecS_USA %>%
add_title("Backup Energy Inputs for Electricity Load Segments Intermittent Technologies") %>%
add_units("none") %>%
add_comments("Backup Energy Inputs for Electricity Load Segments Intermittent Technologies") %>%
add_legacy_name("L2233.StubTechMarket_backup_elec") %>%
add_precursors("L2234.StubTechMarket_backup_elecS_USA",
"gcam-usa/A23.elecS_tech_mapping_cool") ->
L2233.StubTechMarket_backup_elecS_cool_USA
L2233.StubTechInterp_elecS_cool_USA %>%
add_title("Electricity Load Segments Stub Tech Interpolation Rules") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Stub Tech Interpolation Rules - fixed at calibration values") %>%
add_legacy_name("L2233.StubTechShrwt_elec") %>%
same_precursors_as(L2233.StubTechProd_elec_USA) %>%
same_precursors_as(L2233.SubsectorShrwt_elecS_cool_USA) %>%
add_precursors("gcam-usa/A23.elecS_tech_mapping_cool_shares_fut") ->
L2233.StubTechInterp_elecS_cool_USA
L2233.StubTechShrwt_elecS_cool_USA %>%
add_title("Electricity Load Segments Cooling Technology Stub Tech Shareweights") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Cooling Technology Stub Tech Shareweights") %>%
add_legacy_name("L2233.StubTechShrwt_elec") %>%
same_precursors_as(L2233.StubTechInterp_elecS_cool_USA) ->
L2233.StubTechShrwt_elecS_cool_USA
L2233.SubsectorLogit_elecS_USA %>%
add_title("Nested Subsector Information for Horizontal Electricity Load Segments",overwrite=TRUE) %>%
add_units("none") %>%
add_comments("Nested Subsector Information for Horizontal Electricity Load Segments") %>%
add_legacy_name("L223.SubsectorLogit_elec") %>%
add_precursors("L2234.SubsectorLogit_elecS_USA") ->
L2233.SubsectorLogit_elecS_USA
L2233.SubsectorLogit_elecS_cool_USA %>%
add_title("Subsector Information for Horizontal Electricity Load Segments with Cooling Technologies",overwrite=TRUE) %>%
add_units("none") %>%
add_comments("Subsector Information for Horizontal Electricity Load Segments with Cooling Technologies") %>%
add_legacy_name("L2233.SubsectorLogit_elec_cool") %>%
add_precursors("L2234.SubsectorLogit_elecS_USA") ->
L2233.SubsectorLogit_elecS_cool_USA
L2233.SubsectorShrwt_elecS_USA %>%
add_title("Nested Electricity Load Segments Subsector Shareweights") %>%
add_units("none") %>%
add_comments("Nested Electricity Load Segments Subsector Shareweights") %>%
add_legacy_name("L2233.SubsectorShrwt_elec") %>%
add_precursors("L2234.SubsectorShrwt_elecS_USA") ->
L2233.SubsectorShrwt_elecS_USA
L2233.SubsectorShrwt_elecS_cool_USA %>%
add_title("Electricity Load Segments and Cooling Technology Subsector Shareweights") %>%
add_units("none") %>%
add_comments("Electricity Load Segments and Cooling Technology Subsector Shareweights") %>%
add_legacy_name("L2233.SubsectorShrwt_elec") %>%
add_precursors("L2234.StubTechProd_elecS_USA") ->
L2233.SubsectorShrwt_elecS_cool_USA
L2233.SubsectorShrwtInterp_elecS_USA %>%
add_title("Electricity Load Segments Nesting-Subsector Shareweight Interpolation") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Nesting-Subsector Shareweight Interpolation") %>%
add_legacy_name("L2233.SubsectorShrwtInterp_elec") %>%
add_precursors("L2234.SubsectorShrwtInterp_elecS_USA") ->
L2233.SubsectorShrwtInterp_elecS_USA
L2233.SubsectorShrwtInterpTo_elecS_USA %>%
add_title("Electricity Load Segments Nesting-Subsector Shareweight Interpolation") %>%
add_units("none") %>%
add_comments("Electricity Load Segments Nesting-Subsector Shareweight Interpolation") %>%
add_legacy_name("L2233.SubsectorShrwtInterpTo_elec") %>%
add_precursors("L2234.SubsectorShrwtInterpTo_elecS_USA") ->
L2233.SubsectorShrwtInterpTo_elecS_USA
L2233.Supplysector_elecS_USA %>%
add_title("Supply Sector Information for Electricity Load Segments") %>%
add_units("none") %>%
add_comments("Supply Sector Information for Electricity Load Segments") %>%
add_legacy_name("L2233.Supplysector_elec") %>%
add_precursors("L2234.Supplysector_elecS_USA") ->
L2233.Supplysector_elecS_cool_USA
return_data(L2233.GlobalTechEff_elecS_cool_USA,
L2233.GlobalTechShrwt_elecS_cool_USA,
L2233.GlobalTechProfitShutdown_elecS_cool_USA,
L2233.GlobalTechOMvar_elecS_cool_USA,
L2233.GlobalTechOMfixed_elecS_cool_USA,
L2233.GlobalTechCapital_elecS_USA,
L2233.GlobalTechCapital_elecS_cool_USA,
L2233.GlobalTechCapFac_elecS_cool_USA,
L2233.GlobalTechSCurve_elecS_cool_USA,
L2233.GlobalTechCoef_elecS_cool_USA,
L2233.GlobalTechCapture_elecS_cool_USA,
L2233.GlobalTechLifetime_elecS_cool_USA,
L2233.AvgFossilEffKeyword_elecS_cool_USA,
L2233.GlobalIntTechBackup_elecS_cool_USA,
L2233.GlobalIntTechCapital_elecS_USA,
L2233.GlobalIntTechCapital_elecS_cool_USA,
L2233.GlobalIntTechEff_elecS_USA,
L2233.GlobalIntTechEff_elecS_cool_USA,
L2233.GlobalIntTechLifetime_elecS_cool_USA,
L2233.GlobalIntTechOMfixed_elecS_cool_USA,
L2233.GlobalIntTechOMvar_elecS_cool_USA,
L2233.GlobalIntTechShrwt_elecS_cool_USA,
L2233.GlobalIntTechCoef_elecS_cool_USA,
L2233.PrimaryRenewKeyword_elecS_cool_USA,
L2233.PrimaryRenewKeywordInt_elecS_cool_USA,
L2233.StubTechEff_elecS_cool_USA,
L2233.StubTechCoef_elecS_cool_USA,
L2233.StubTechMarket_elecS_cool_USA,
L2233.StubTechProd_elecS_cool_USA,
L2233.StubTechSCurve_elecS_cool_USA,
L2233.StubTechCapFactor_elecS_solar_USA,
L2233.StubTechCapFactor_elecS_wind_USA,
L2233.StubTechElecMarket_backup_elecS_cool_USA,
L2233.StubTechFixOut_elecS_cool_USA,
L2233.StubTechFixOut_hydro_elecS_cool_USA,
L2233.StubTechMarket_backup_elecS_cool_USA,
L2233.StubTechProfitShutdown_elecS_cool_USA,
L2233.StubTechShrwt_elecS_cool_USA,
L2233.StubTechInterp_elecS_cool_USA,
L2233.SubsectorLogit_elecS_USA,
L2233.SubsectorLogit_elecS_cool_USA,
L2233.SubsectorShrwt_elecS_USA,
L2233.SubsectorShrwt_elecS_cool_USA,
L2233.SubsectorShrwtInterp_elecS_USA,
L2233.StubTechCost_offshore_wind_elecS_cool_USA,
L2233.SubsectorShrwtInterpTo_elecS_USA,
L2233.Supplysector_elecS_cool_USA)
} else {
stop("Unknown command")
}
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.