R/reportCosts.R
In pik-piam/remind: The REMIND R Package
Defines functions
reportCosts
Documented in
reportCosts
#' Read in GDX and calculate costs, used in convGDX2MIF.R for the reporting
#'
#' Read in cost information from GDX file, information used in convGDX2MIF.R
#' for the reporting
#'
#'
#' @param gdx a GDX object as created by readGDX, or the path to a gdx
#' @param output a magpie object containing all needed variables generated by other report*.R functions
#' @param regionSubsetList a list containing regions to create report variables region
#' aggregations. If NULL (default value) only the global region aggregation "GLO" will
#' be created.
#' @return MAgPIE object - contains the cost variables
#' @author David Klein
#' @seealso \code{\link{convGDX2MIF}}
#' @examples
#'
#' \dontrun{reportCosts(gdx)}
#'
#' @export
#' @importFrom rlang .data
#' @importFrom magclass mbind getYears collapseNames dimSums setNames
#' @importFrom gdx readGDX
#' @importFrom dplyr filter
reportCosts <- function(gdx,output=NULL,regionSubsetList=NULL) {
# Cost calculation requires information from other reportings
if(is.null(output)){
cat("Executing reportExtraction\n")
output <- mbind(output,reportExtraction(gdx,regionSubsetList))
cat("Executing reportPrices\n")
output <- mbind(output,reportPrices(gdx,regionSubsetList=regionSubsetList))
cat("Executing reportEnergyInvestments\n")
output <- mbind(output,reportEnergyInvestment(gdx,regionSubsetList)[,getYears(output),])
}
########################################################################################
############# R E A D I N G I N P U T ###############################################
########################################################################################
# module realisations
module2realisation <- readGDX(gdx, "module2realisation", react = "silent")
industry_module <- module2realisation['industry' == module2realisation$modules, 2]
# Mappings
ccs2te <- readGDX(gdx,"ccs2te")
enty2rlf <- readGDX(gdx,c("pe2rlf","enty2rlf"),format="first_found")
teall2rlf <- readGDX(gdx,c("te2rlf","teall2rlf"),format="first_found")
pe2se <- readGDX(gdx,"pe2se")
se2fe <- readGDX(gdx,"se2fe")
se2se <- readGDX(gdx,c("se2se"),format="first_found")
# Sets
tenoccs <- readGDX(gdx,c("teNoCCS","tenoccs"),format="first_found")
temapall <- readGDX(gdx,c("en2en","temapall"),format="first_found")
tenotransform<- readGDX(gdx,c("teNoTransform","tenotransform"),format="first_found")
stor <- readGDX(gdx,c("teStor","stor"),format="first_found")
grid <- readGDX(gdx,c("teGrid","grid"),format="first_found")
trade_pe <- readGDX(gdx,c("tradePe","trade_pe"),format="first_found")
perenew <- readGDX(gdx,c("peRe","perenew"),format="first_found")
petyf <- readGDX(gdx,c("peFos","petyf"),format="first_found")
sety <- readGDX(gdx,c("entySe","sety"),format="first_found")
fety <- readGDX(gdx,c("entyFe","fety"),format="first_found")
potentialseLiq <- c("seliq","sepet","sedie") # the sety liquids changed from sepet+sedie to seLiq in REMIND 1.7
se_Liq <- intersect(potentialseLiq,sety)
teccs <- readGDX(gdx,c("teCCS","teccs"),format="first_found")
pebio <- readGDX(gdx,c("peBio","pebio"),format="first_found")
ppfen_stat <- readGDX(gdx,c("ppfen_stationary_dyn38","ppfen_stationary_dyn28","ppfen_stationary"),format="first_found", react = "silent")
if (length(ppfen_stat) == 0) ppfen_stat = NULL
fe2ppfen37 <- readGDX(gdx, 'fe2ppfen37', react = 'silent')
emiMacMagpie <- readGDX(gdx,c("emiMacMagpie"),format="first_found")
emiMacMagpieN2O <- readGDX(gdx,c("emiMacMagpieN2O"),format="first_found")
emiMacMagpieCH4 <- readGDX(gdx,c("emiMacMagpieCH4"),format="first_found")
emiMacMagpieCO2 <- readGDX(gdx,c("emiMacMagpieCO2"),format="first_found")
# Parameters
pm_conv_TWa_EJ <- 31.536
sm_tdptwyr2dpgj <- 31.71 #TerraDollar per TWyear to Dollar per
pm_data <- readGDX(gdx,name="pm_data",format="first_found")
pm_petradecost2_Mp_fin <- readGDX(gdx,name="pm_petradecost2_Mp_fin",format="first_found", react = "silent")
if(is.null(pm_petradecost2_Mp_fin)){
pm_petradecost2_Mp_fin <- readGDX(gdx,name="pm_costsTradePeFinancial",format="first_found")
pm_petradecost2_Mp_fin <- collapseNames(pm_petradecost2_Mp_fin[,,"Mport"])
}
p_dataeta <- readGDX(gdx,name=c("pm_dataeta","p_dataeta"),format="first_found")
pm_pvp <- readGDX(gdx,name=c("pm_pvp"),format = "first_found")
cost_emu_pre <- readGDX(gdx,name="p30_pebiolc_costs_emu_preloop",format="first_found")
cost_mag <- readGDX(gdx,name="p30_pebiolc_costsmag",format="first_found")[,getYears(cost_emu_pre),]
totLUcosts <- readGDX(gdx,name=c("pm_totLUcosts"),format="first_found")[,getYears(cost_emu_pre),]
totLUcostsWithMAC <- readGDX(gdx,name=c("p26_totLUcosts_withMAC"),format="first_found")[,getYears(cost_emu_pre),]
costsLuMACLookup <- readGDX(gdx,name=c("p26_macCostLu"),format="first_found")[,getYears(cost_emu_pre),]
costsMAC <- readGDX(gdx,name=c("pm_macCost","p_macCost"),format="first_found")[,getYears(cost_emu_pre),]
p_eta_conv <- readGDX(gdx,name=c("pm_eta_conv","p_eta_conv"),format = "first_found")
# Variables
Xport <- readGDX(gdx,name=c("vm_Xport"), field = "l",format = "first_found")
Mport <- readGDX(gdx,name=c("vm_Mport"), field = "l",format = "first_found")
vm_fuelex <- readGDX(gdx,name=c("vm_fuExtr","vm_fuelex"), field="l",restore_zeros=FALSE,format="first_found")[enty2rlf]
vm_costfu_ex <- readGDX(gdx,name=c("vm_costFuEx","vm_costfu_ex"), field="l",restore_zeros=FALSE,format="first_found")
v_costfu <- readGDX(gdx,name=c("v_costFu","v_costfu"), field="l",restore_zeros=FALSE,format="first_found")
v_costom <- readGDX(gdx,name=c("v_costOM","v_costom"), field="l", format="first_found")
v_costin <- readGDX(gdx,name=c("v_costInv","v_costin"), field = "l",format = "first_found")
vm_omcosts_cdr <- readGDX(gdx,name=c("vm_omcosts_cdr"), field="l", format="first_found")
vm_otherFEdemand <- readGDX(gdx,name=c("vm_otherFEdemand"), field="l",restore_zeros=FALSE,format="first_found")
v_investcost <- readGDX(gdx,name=c("vm_costTeCapital","v_costTeCapital","v_investcost"), field="l",format="first_found")
vm_cap <- readGDX(gdx,name=c("vm_cap"), field="l",format="first_found")
vm_cap[is.na(vm_cap)] <- 0
vm_prodSe <- readGDX(gdx,name=c("vm_prodSe"), field="l",restore_zeros=FALSE,format="first_found")
vm_prodFe <- readGDX(gdx,name=c("vm_prodFe"), field="l",restore_zeros=FALSE,format="first_found")
cost_emu <- readGDX(gdx,name=c("v30_pebiolc_costs"),field="l",format="first_found")
bio_cost_adjfac <- readGDX(gdx,name=c("v30_multcost"),field="l",format="first_found")
vm_cesIO <- readGDX(gdx, name = c('vm_cesIO'), field = 'l',
restore_zeros = FALSE)
# Equations
finenbal <- readGDX(gdx,name=c("fe2ppfEn","finenbal"), types="sets",format="first_found")
pebal.m <- readGDX(gdx,name=c("q_balPe","qm_pebal"), types="equations",field="m",format="first_found")
budget.m <- readGDX(gdx,name='qm_budget', types="equations",field="m",format="first_found") # alternative: calcPrice
sebal.m <- readGDX(gdx,name=c("q_balSe","q_sebal"), types="equations",field="m",format="first_found")
febal.m <- readGDX(gdx,name=c("q_balFe","q_febal"), types="equations",field="m",format="first_found")[,,fety]
balfinen.m <- readGDX(gdx,name=c("qm_balFeForCesAndEs","qm_balFeForCes","q_balFeForCes","q_balfinen"),types="equations",field="m",format="first_found")[finenbal]
# Find common years
y <- Reduce(intersect,list(getYears(vm_fuelex),
getYears(vm_costfu_ex),
getYears(p_dataeta),
getYears(v_investcost),
getYears(vm_cap),
getYears(vm_prodSe)))
# Reduce to common years
p_dataeta <- p_dataeta[,y,]
pm_pvp <- pm_pvp[,y,]
vm_fuelex <- vm_fuelex[,y,]
Xport <- Xport[,y,]
Mport <- Mport[,y,]
vm_costfu_ex <- vm_costfu_ex[,y,]
v_costfu <- v_costfu[,y,]
v_costom <- v_costom[,y,]
v_costin <- v_costin[,y,]
vm_otherFEdemand <- vm_otherFEdemand[,y,]
v_investcost <- v_investcost[,y,]
vm_cap <- vm_cap[,y,]
vm_prodSe <- vm_prodSe[,y,]
pebal.m <- pebal.m[,y,]
budget.m <- budget.m[,y,]
sebal.m <- sebal.m[,y,]
febal.m <- febal.m[,y,]
balfinen.m <- balfinen.m[,y,]
vm_omcosts_cdr <- vm_omcosts_cdr[,y,]
output <- output[,y,]
p_eta_conv <- p_eta_conv[,y,]
# Gather efficiency data in only one magpie object to enable generic structure of below defined functions:
# Take values from pm_data (constant efficiency over time) for technologies where p_dataeta (time variant efficiencies) has no values.
# Thus, in the below defined formulas time variant efficiencies will be used if available otherwise time invariant
for (te in magclass::getNames(p_dataeta)) {
if(all(p_dataeta[,,te]==0)) {
for (year in getYears(p_dataeta)) {
p_dataeta[,year,te] <- pm_data[,,"eta"][,,te]
}
}
}
########################################################################################
############# F U N C T I O N S D E F I N I T I O N #################################
########################################################################################
op_costs_part2_foss <- function(pe,se,te,vm_prodSe,i_pe2se,p_dataeta,vm_costfu_ex,vm_fuelex,sm_tdptwyr2dpgj,pm_conv_TWa_EJ) {
sub_pe2se <- i_pe2se[(pe2se$all_enty %in% pe) & (i_pe2se$all_enty1 %in% se) & (i_pe2se$all_te %in% te),]
out <- dimSums( vm_costfu_ex[,,pe] / dimSums(vm_fuelex[,,pe],dim = 3, na.rm = T), dim = 3, na.rm = T) * sm_tdptwyr2dpgj * # Average supply costs
dimSums( vm_prodSe[sub_pe2se] / p_dataeta[,,sub_pe2se$all_te], dim = 3, na.rm = T) * pm_conv_TWa_EJ
return(out)
}
op_costs_part2_bio_nuc <- function(pe,se,te,vm_prodSe,i_pe2se,p_dataeta,pm_conv_TWa_EJ) {
sub_pe2se <- i_pe2se[(pe2se$all_enty %in% pe) & (i_pe2se$all_enty1 %in% se) & (i_pe2se$all_te %in% te),]
out <- dimSums( vm_prodSe[sub_pe2se] / p_dataeta[,,sub_pe2se$all_te], dim = 3, na.rm = T) * pm_conv_TWa_EJ
return(out)
}
# operation and maintenance costs
op_costs <- function(ei,eo,te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost) {
# Check whether a mapping with energy transfering technologies is given or just technologies
if (!is.null(e2e)) {
sub_e2e <- e2e[(e2e$all_enty %in% ei) & (e2e$all_enty1 %in% eo) & (e2e$all_te %in% te),]
# Save technologies to extra variables because in the "else" case there is no sub_e2e list that could be used
e2e_allte <- sub_e2e$all_te
} else {
e2e_allte <- te
}
vm_cap <- dimSums(vm_cap,dim=3.2,na.rm=T) # get rid of grades which are not used in calculations below because all other variables dont have them neither
out <- dimSums( # sum OMF over technologies
collapseNames(pm_data[,,"omf"])[,,e2e_allte] *
(dimSums((v_investcost[,,e2e_allte] * vm_cap[,,e2e_allte])[teall2rlf],dim=3.2,na.rm=T) # sum over rlf
)[,, e2e_allte],dim = 3, na.rm = T)
if(!is.null(vm_prodE) & !length(e2e_allte)==0) { # if either SE or FE is produced, then variable O&M is added
out <- out + dimSums(collapseNames(pm_data[,,"omv"])[,,sub_e2e$all_te] * dimSums(vm_prodE[sub_e2e],dim=c(3.1,3.2),na.rm=T)
, dim = 3, na.rm = T)
}
out <- out * 1000
return(out)
}
cost_Mport <- function(pety,pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport) {
out <- dimSums((pm_petradecost2_Mp_fin[,,pety] + (pm_pvp[,,pety] / (budget.m + 1.e-10))) * Mport[,,pety], dim = 3, na.rm = T) * 1000
return(out)
}
########################################################################################
############# O U T P U T G E N E R A T I O N ########################################
########################################################################################
# Initialize empty object that will be filled with reporting results
tmp <- NULL
# Calculate and append new variables to magpie object
#######################################
########## Biomass costs ##############
#######################################
if(!is.null(cost_mag)) {tmp <- mbind(tmp,setNames(cost_mag * 1000, "Costs|Biomass|MAgPIE (billion US$2005/yr)"))}
tmp <- mbind(tmp,setNames(cost_emu_pre * 1000, "Costs|Biomass|Price integral presolve (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(cost_emu * 1000, "Costs|Biomass|Price integral (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(bio_cost_adjfac, "Costs|Biomass|Adjfactor (-)"))
if(!is.null(totLUcosts)) {tmp <- mbind(tmp,setNames(totLUcosts * 1000, "Costs|Land Use (billion US$2005/yr)"))}
if(!is.null(totLUcostsWithMAC)) {tmp <- mbind(tmp,setNames(totLUcostsWithMAC * 1000, "Costs|Land Use with MAC-costs from MAgPIE (billion US$2005/yr)"))}
if(!is.null(costsLuMACLookup)) {tmp <- mbind(tmp,setNames(costsLuMACLookup * 1000, "Costs|Land Use|MAC-costs Lookup (billion US$2005/yr)"))}
if(!is.null(getNames(costsMAC))) tmp <- mbind(tmp,setNames(dimSums(costsMAC[,,emiMacMagpie], dim = 3, na.rm = T) * 1000, "Costs|Land Use|MAC-costs (billion US$2005/yr)"))
if(!is.null(getNames(costsMAC))) tmp <- mbind(tmp,setNames(dimSums(costsMAC[,,emiMacMagpieN2O],dim = 3, na.rm = T) * 1000, "Costs|Land Use|MAC-costs|N2O (billion US$2005/yr)"))
if(!is.null(getNames(costsMAC))) tmp <- mbind(tmp,setNames(dimSums(costsMAC[,,emiMacMagpieCH4],dim = 3, na.rm = T) * 1000, "Costs|Land Use|MAC-costs|CH4 (billion US$2005/yr)"))
if(!is.null(getNames(costsMAC))) tmp <- mbind(tmp,setNames(dimSums(costsMAC[,,emiMacMagpieCO2],dim = 3, na.rm = T) * 1000, "Costs|Land Use|MAC-costs|CO2 (billion US$2005/yr)"))
tmp <- tmp[,y,]
#######################################
########## Fuel Costs #################
#######################################
##### Total
tmp <- mbind(tmp,setNames(v_costfu * 1000, "Fuel supply costs (billion US$2005/yr)"))
##### Fuel costs for own ESM
regi_on_gdx <- unique(readGDX(gdx, name = "regi2iso")[,1])
# v_costfu: these costs are the total fuel extraction costs, even the ones for export
# Supply costs: exports valued at supply cost (else the ESM costs would be greatly underestimated for a resource-exporting country that makes large profits from the export), except for biomass where supply costs are not yet reported
cost <- v_costfu * 1000 - setNames(output[regi_on_gdx,,"Res|Average Supply Costs|Coal ($/GJ)"] * Xport[,,"pecoal"] * pm_conv_TWa_EJ,NULL) -
setNames(output[regi_on_gdx,,"Res|Average Supply Costs|Gas ($/GJ)"] * Xport[,,"pegas"] * pm_conv_TWa_EJ,NULL) -
setNames(output[regi_on_gdx,,"Res|Average Supply Costs|Oil ($/GJ)"] * Xport[,,"peoil"] * pm_conv_TWa_EJ,NULL) -
setNames(output[regi_on_gdx,,"Price|Biomass|Primary Level (US$2005/GJ)"] * Xport[,,"pebiolc"] * pm_conv_TWa_EJ,NULL) -
setNames(output[regi_on_gdx,,"Res|Average Supply Costs|Uranium ($/GJ)"] * Xport[,,"peur"] * pm_conv_TWa_EJ * 4.43,NULL) +
dimSums(Mport[,,trade_pe] * pebal.m[,,trade_pe] / (budget.m + 1.e-10), dim = 3, na.rm = T) * 1000 # imports valued with domestic market price
tmp <- mbind(tmp,setNames(cost, "Fuel costs for own ESM (billion US$2005/yr)"))
##### Import fuel costs
cost<- cost_Mport(trade_pe,pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport)
tmp <- mbind(tmp,setNames(cost, "Import Fuel costs (billion US$2005/yr)"))
###### Import fuel costs|Coal
cost<- cost_Mport("pecoal",pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport)
tmp <- mbind(tmp,setNames(cost, "Import Fuel costs|Coal (billion US$2005/yr)"))
###### Import fuel costs|Gas
cost<- cost_Mport("pegas",pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport)
tmp <- mbind(tmp,setNames(cost, "Import Fuel costs|Gas (billion US$2005/yr)"))
###### Import fuel costs|Oil
cost<- cost_Mport("peoil",pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport)
tmp <- mbind(tmp,setNames(cost, "Import Fuel costs|Oil (billion US$2005/yr)"))
###### Import fuel costs|Uranium
cost<- cost_Mport("peur",pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport)
tmp <- mbind(tmp,setNames(cost, "Import Fuel costs|Uranium (billion US$2005/yr)"))
###### Import fuel costs|Pebiolc
cost<- cost_Mport("pebiolc",pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport)
tmp <- mbind(tmp,setNames(cost, "Import Fuel costs|Biomass (billion US$2005/yr)"))
###### Export Fuel Costs|Coal
cost <- output[regi_on_gdx,,"Res|Average Supply Costs|Coal ($/GJ)"] * Xport[,,"pecoal"] * pm_conv_TWa_EJ
tmp <- mbind(tmp,setNames(cost, "Export Fuel costs|Coal (billion US$2005/yr)"))
###### Export Fuel Costs|Gas
cost <- output[regi_on_gdx,,"Res|Average Supply Costs|Gas ($/GJ)"] * Xport[,,"pegas"] * pm_conv_TWa_EJ
tmp <- mbind(tmp,setNames(cost, "Export Fuel costs|Gas (billion US$2005/yr)"))
###### Export Fuel Costs|Oil
cost <- output[regi_on_gdx,,"Res|Average Supply Costs|Oil ($/GJ)"] * Xport[,,"peoil"] * pm_conv_TWa_EJ
tmp <- mbind(tmp,setNames(cost, "Export Fuel costs|Oil (billion US$2005/yr)"))
###### Export Fuel Costs|Biomass
#cost <- output[regi_on_gdx,,"Res|Average Supply Costs|Biomass ($/GJ)"] * Xport[,,"pebiolc"]
#tmp <- mbind(tmp,setNames(cost, "Export Fuel costs|Biomass (billion US$2005/yr)"))
###### Export Fuel Costs|Uranium
cost <- output[regi_on_gdx,,"Res|Average Supply Costs|Uranium ($/GJ)"] * Xport[,,"peur"] * p_eta_conv[,,"tnrs"] * pm_conv_TWa_EJ
tmp <- mbind(tmp,setNames(cost, "Export Fuel costs|Uranium (billion US$2005/yr)"))
#######################################
########## Energy System costs ########
#######################################
cost <- (v_costin + v_costom) * 1000 + tmp[,,"Fuel costs for own ESM (billion US$2005/yr)"]
tmp <- mbind(tmp,setNames(cost,"Energy system costs (billion US$2005/yr)"))
#######################################
########## Energy costs ###############
#######################################
if (!is.null(ppfen_stat)){
##### CDR
price_feels <- abs(balfinen.m[,,"feels.feels"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Electricity|Stationary (US$2005/GJ)")
price_fedie <- abs(febal.m[,,"fedie"] /(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Diesel (US$2005/GJ)")
price_fehes <- abs(balfinen.m[,,"fehes.fehes"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Heat|
price_fegas <- abs(balfinen.m[,,"fegas.fegas"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Gas (US$2005/GJ)")
price_feh2s <- abs(balfinen.m[,,"feh2s.feh2s"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Hydrogen|Stationary (US$2005/GJ)")
# reduce names in 3rd dimension
price_feels <- setNames(price_feels,"feels") # reduce feels.feels to feels
price_fehes <- setNames(price_fehes,"fehes") # reduce fehes.fehes to fehes
price_fegas <- setNames(price_fegas,"fegas") # reduce fegas.fegas to fegas
price_feh2s <- setNames(price_feh2s,"feh2s") # reduce feh2s.feh2s to feh2s
tmp <- mbind(tmp,setNames(price_feels * vm_otherFEdemand[,,"feels"] * pm_conv_TWa_EJ, "Energy costs CDR|Electricity (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(price_fedie * vm_otherFEdemand[,,"fedie"] * pm_conv_TWa_EJ, "Energy costs CDR|Diesel (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames((price_fegas * vm_otherFEdemand[,,"fegas"] + price_feh2s * vm_otherFEdemand[,,"feh2s"]) * pm_conv_TWa_EJ, "Energy costs CDR|Heat (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(price_feels * vm_otherFEdemand[,,"feels"] * pm_conv_TWa_EJ +
price_fedie * vm_otherFEdemand[,,"fedie"] * pm_conv_TWa_EJ +
price_fehes * vm_otherFEdemand[,,"fehes"] * pm_conv_TWa_EJ,
"Energy costs CDR (billion US$2005/yr)"))
} else {
if ('subsectors' == industry_module) {
fe2ppfen37_feels <- filter(fe2ppfen37, 'feels' == .data$all_enty)
fe2ppfen37_fegas <- filter(fe2ppfen37, 'fegas' == .data$all_enty)
fe2ppfen37_feh2s <- filter(fe2ppfen37, 'feh2s' == .data$all_enty)
# "Price|Final Energy|Electricity|Industry (US$2005/GJ)")
price_feeli <- abs(
( dimSums(
mselect(balfinen.m, fe2ppfen37_feels)
* vm_cesIO[,y,fe2ppfen37_feels$all_in],
dim = 3, na.rm = T)
/ dimSums(vm_cesIO[,y,fe2ppfen37_feels$all_in], dim = 3, na.rm = T)
)
/ (budget.m + 1e-10) * 1000 / pm_conv_TWa_EJ
)
# "Price|Final Energy|Gases|Industry (US$2005/GJ)")
price_fegai <- abs(
( dimSums(
mselect(balfinen.m, fe2ppfen37_fegas)
* vm_cesIO[,y,fe2ppfen37_fegas$all_in],
dim = 3, na.rm = T)
/ dimSums(vm_cesIO[,y,fe2ppfen37_fegas$all_in], dim = 3, na.rm = T)
)
/ (budget.m + 1e-10) * 1000 / pm_conv_TWa_EJ
)
# "Price|Final Energy|Hydrogen|Industry (US$2005/GJ)")
price_feh2i <- abs(
( dimSums(
mselect(balfinen.m, fe2ppfen37_feh2s)
* vm_cesIO[,y,fe2ppfen37_feh2s$all_in],
dim = 3, na.rm = T)
/ dimSums(vm_cesIO[,y,fe2ppfen37_feh2s$all_in], dim = 3, na.rm = T)
)
/ (budget.m + 1e-10) * 1000 / pm_conv_TWa_EJ
)
} else {
price_feeli <- abs(balfinen.m[,,"feels.feeli"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Electricity|Industry (US$2005/GJ)")
price_fegai <- abs(balfinen.m[,,"fegas.fegai"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Gases|Industry (US$2005/GJ)")
price_feh2i <- abs(balfinen.m[,,"feh2s.feh2i"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Hydrogen|Industry (US$2005/GJ)")
}
price_fedie <- abs(febal.m[,,"fedie"] /(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Diesel (US$2005/GJ)")
# reduce names in 3rd dimension
price_feeli <- setNames(price_feeli,"feeli") # reduce feels.feels to feels
price_fegai <- setNames(price_fegai,"fegai") # reduce fehes.fehes to fehes
price_feh2i <- setNames(price_feh2i,"feh2i") # reduce fehes.fehes to fehes
tmp <- mbind(tmp,setNames(price_feeli * vm_otherFEdemand[,,"feels"] * pm_conv_TWa_EJ , "Energy costs CDR|Electricity (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(price_fedie * vm_otherFEdemand[,,"fedie"] * pm_conv_TWa_EJ, "Energy costs CDR|Diesel (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(price_fegai * vm_otherFEdemand[,,"fegas"] * pm_conv_TWa_EJ +
price_feh2i * vm_otherFEdemand[,,"feh2s"] * pm_conv_TWa_EJ, "Energy costs CDR|Heat (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(price_feeli * vm_otherFEdemand[,,"feels"] * pm_conv_TWa_EJ +
price_fedie * vm_otherFEdemand[,,"fedie"] * pm_conv_TWa_EJ +
price_fegai * vm_otherFEdemand[,,"fegas"] * pm_conv_TWa_EJ +
price_feh2i * vm_otherFEdemand[,,"feh2s"] * pm_conv_TWa_EJ,
"Energy costs CDR (billion US$2005/yr)"))
}
#######################################
########## Total Energy costs #########
#######################################
##### Total
cost1 <- op_costs(ei=temapall$all_enty,eo=sety,te=teall2rlf$all_te,e2e=temapall,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs(ei=temapall$all_enty,eo=fety,te=teall2rlf$all_te,e2e=temapall,teall2rlf=teall2rlf,vm_prodE=vm_prodFe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost3 <- op_costs(ei=NULL,eo=NULL,te=tenotransform,e2e=NULL,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost1 + cost2 + cost3 + output[regi_on_gdx,,"Energy Investments|Supply (billion US$2005/yr)"], "Total Energy costs (billion US$2005/yr)"))
##### Electricity
cost1 <- op_costs(ei=pe2se$all_enty,eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs(ei="seel",eo=se2fe$all_enty1,te=se2fe$all_te,e2e=se2fe,teall2rlf=teall2rlf,vm_prodE=vm_prodFe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost3 <- op_costs(ei=NULL,eo=NULL,te=tenotransform,e2e=NULL,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost1 + cost2 + cost3 + output[regi_on_gdx,,"Energy Investments|Electricity (billion US$2005/yr)"], "Total Energy costs|Electricity (billion US$2005/yr)"))
##### Elec|Fossil
cost <- op_costs(ei=petyf,eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Fossil (billion US$2005/yr)"], "Total Energy costs|Elec|Fossil (billion US$2005/yr)"))
##### Elec|Non-fossil
cost <- op_costs(ei=setdiff(pe2se$all_enty,petyf),eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Non-Fossil (billion US$2005/yr)"], "Total Energy costs|Elec|Non-Fossil (billion US$2005/yr)"))
##### Elec|Biomass
cost <- op_costs(ei="pebiolc",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Biomass (billion US$2005/yr)"], "Total Energy costs|Elec|Biomass (billion US$2005/yr)"))
cost <- op_costs(ei="pebiolc",eo="seel",te=teccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Biomass|w/ CCS (billion US$2005/yr)"], "Total Energy costs|Elec|Biomass|w/ CCS (billion US$2005/yr)"))
cost <- op_costs(ei="pebiolc",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Biomass|w/o CCS (billion US$2005/yr)"], "Total Energy costs|Elec|Biomass|w/o CCS (billion US$2005/yr)"))
##### Elec|Coal
cost <- op_costs(ei="pecoal",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost <- cost + output[regi_on_gdx,,"Energy Investments|Elec|Coal (billion US$2005/yr)"]
tmp <- mbind(tmp,setNames(cost, "Total Energy costs|Elec|Coal (billion US$2005/yr)"))
cost <- op_costs(ei="pecoal",eo="seel",te=teccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost <- cost + output[regi_on_gdx,,"Energy Investments|Elec|Coal|w/ CCS (billion US$2005/yr)"]
tmp <- mbind(tmp,setNames(cost, "Total Energy costs|Elec|Coal|w/ CCS (billion US$2005/yr)"))
cost <- op_costs(ei="pecoal",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost <- cost + output[regi_on_gdx,,"Energy Investments|Elec|Coal|w/o CCS (billion US$2005/yr)"]
tmp <- mbind(tmp,setNames(cost, "Total Energy costs|Elec|Coal|w/o CCS (billion US$2005/yr)"))
##### Elec|Gas
cost <- op_costs(ei="pegas",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Gas (billion US$2005/yr)"], "Total Energy costs|Elec|Gas (billion US$2005/yr)"))
cost <- op_costs(ei="pegas",eo="seel",te=teccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Gas|w/ CCS (billion US$2005/yr)"], "Total Energy costs|Elec|Gas|w/ CCS (billion US$2005/yr)"))
cost <- op_costs(ei="pegas",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Gas|w/o CCS (billion US$2005/yr)"], "Total Energy costs|Elec|Gas|w/o CCS (billion US$2005/yr)"))
##### Elec|Oil
cost <- op_costs(ei="peoil",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Oil (billion US$2005/yr)"], "Total Energy costs|Elec|Oil (billion US$2005/yr)"))
cost <- op_costs(ei="peoil",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Oil|w/o CCS (billion US$2005/yr)"], "Total Energy costs|Elec|Oil|w/o CCS (billion US$2005/yr)"))
##### Elec|Nuclear
cost <- op_costs(ei="peur",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Nuclear (billion US$2005/yr)"], "Total Energy costs|Elec|Nuclear (billion US$2005/yr)"))
##### Elec|Non-biomass renewables
cost <- op_costs(ei=setdiff(perenew,pebio),eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Non-Bio Re (billion US$2005/yr)"], "Total Energy costs|Elec|Non-Bio Re (billion US$2005/yr)"))
##### Elec|Solar
cost <- op_costs(ei="pesol",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Solar (billion US$2005/yr)"], "Total Energy costs|Elec|Solar (billion US$2005/yr)"))
##### Elec|Wind
cost <- op_costs(ei="pewin",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Wind (billion US$2005/yr)"], "Total Energy costs|Elec|Wind (billion US$2005/yr)"))
##### Elec|Hydro
cost <- op_costs(ei="pehyd",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Hydro (billion US$2005/yr)"], "Total Energy costs|Elec|Hydro (billion US$2005/yr)"))
##### Elec|Geothermal
cost <- op_costs(ei="pegeo",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Geothermal (billion US$2005/yr)"], "Total Energy costs|Elec|Geothermal (billion US$2005/yr)"))
##### Elec|Hydrogen
if ("h2turb" %in% se2se$all_te) {
cost <- op_costs(ei="seh2",eo="seel",te=se2se$all_te,e2e=se2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Hydrogen (billion US$2005/yr)"], "Total Energy costs|Elec|Hydrogen (billion US$2005/yr)"))
}
##### Elec|Storage
cost <- op_costs(ei=NULL,eo=NULL,te=stor,e2e=NULL,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Storage (billion US$2005/yr)"], "Total Energy costs|Elec|Storage (billion US$2005/yr)"))
##### Elec|Grid
cost1 <- op_costs(ei=NULL,eo=NULL,te=grid,e2e=NULL,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs(ei="seel",eo=se2fe$all_enty1,te=se2fe$all_te,e2e=se2fe,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost1 + cost2 + output[regi_on_gdx,,"Energy Investments|Elec|Grid (billion US$2005/yr)"], "Total Energy costs|Elec|Grid (billion US$2005/yr)"))
##### Heat
#TiA: including investments, and operation and maintenance, BUT excluding input fuel costs
cost_pe2se <- op_costs(ei=pe2se$all_enty,eo="sehe",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost_se2fe <- op_costs(ei="sehe",eo=se2fe$all_enty1,te=se2fe$all_te,e2e=se2fe,teall2rlf=teall2rlf,vm_prodE=vm_prodFe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost_pe2se + cost_se2fe + output[regi_on_gdx,,"Energy Investments|Heat (billion US$2005/yr)"], "Total Energy costs|Heat (billion US$2005/yr)"))
##### Hydrogen
#TiA: including investments, and operation and maintenance, BUT excluding input fuel costs
cost_pe2se <- op_costs(ei=pe2se$all_enty,eo="seh2",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost_se2fe <- op_costs(ei="seh2",eo=se2fe$all_enty1,te=se2fe$all_te,e2e=se2fe,teall2rlf=teall2rlf,vm_prodE=vm_prodFe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost_pe2se + cost_se2fe + output[regi_on_gdx,,"Energy Investments|Hydrogen (billion US$2005/yr)"], "Total Energy costs|Hydrogen (billion US$2005/yr)"))
##### Hydrogen|Fossil
cost <- op_costs(ei=petyf,eo="seh2",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Hydrogen|Fossil (billion US$2005/yr)"], "Total Energy costs|Hydrogen|Fossil (billion US$2005/yr)"))
##### Hydrogen|RE
cost <- op_costs(ei=perenew,eo="seh2",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Hydrogen|RE (billion US$2005/yr)"], "Total Energy costs|Hydrogen|RE (billion US$2005/yr)"))
##### Liquids
#TiA: including investments, and operation and maintenance, BUT excluding input fuel costs
cost_pe2se <- op_costs(ei=pe2se$all_enty,eo=se_Liq,te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost_se2fe <- op_costs(ei=se_Liq,eo=se2fe$all_enty1,te=se2fe$all_te,e2e=se2fe,teall2rlf=teall2rlf,vm_prodE=vm_prodFe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost_pe2se + cost_se2fe + output[regi_on_gdx,,"Energy Investments|Liquids (billion US$2005/yr)"], "Total Energy costs|Liquids (billion US$2005/yr)"))
##### Liquids|Oil Ref
cost <- op_costs(ei="peoil",eo=se_Liq,te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Liquids|Oil Ref (billion US$2005/yr)"], "Total Energy costs|Liquids|Oil Ref (billion US$2005/yr)"))
##### Liquids|Fossil|w/ oil
cost <- op_costs(ei=petyf,eo=se_Liq,te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Liquids|Fossil|w/ oil (billion US$2005/yr)"], "Total Energy costs|Liquids|Fossil|w/ oil (billion US$2005/yr)"))
##### Liquids|Fossil
cost <- op_costs(ei="pecoal",eo=se_Liq,te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Liquids|Fossil (billion US$2005/yr)"], "Total Energy costs|Liquids|Fossil (billion US$2005/yr)"))
##### Liquids|Bio
cost <- op_costs(ei=perenew,eo=se_Liq,te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Liquids|Bio (billion US$2005/yr)"], "Total Energy costs|Liquids|Bio (billion US$2005/yr)"))
##### CO2 Trans&Stor
cost <- op_costs(ei=ccs2te$all_enty,eo=ccs2te$all_enty1,te=ccs2te$all_te,e2e=ccs2te,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|CO2 Trans&Stor (billion US$2005/yr)"], "Total Energy costs|CO2 Trans&Stor (billion US$2005/yr)"))
##### Other
tmp <- mbind(tmp,setNames(tmp[,,"Total Energy costs (billion US$2005/yr)"]-
tmp[,,"Total Energy costs|Electricity (billion US$2005/yr)"]-
tmp[,,"Total Energy costs|Hydrogen (billion US$2005/yr)"]-
tmp[,,"Total Energy costs|Liquids (billion US$2005/yr)"]-
tmp[,,"Total Energy costs|Heat (billion US$2005/yr)"]-
tmp[,,"Total Energy costs|CO2 Trans&Stor (billion US$2005/yr)"],
"Total Energy costs|Other (billion US$2005/yr)"))
#####################################
########## O & M costs ##############
#####################################
ei=temapall$all_enty
eo=sety
te=teall2rlf$all_te
e2e=temapall
##### Total
tmp <- mbind(tmp,setNames(v_costom * 1000, "OandM costs (billion US$2005/yr)"))
##### CDR
tmp <- mbind(tmp,setNames(vm_omcosts_cdr * 1000, "OandM costs CDR (billion US$2005/yr)"))
#####################################
########## Operational costs ########
#####################################
##### Fossils
cost1 <- op_costs(ei="pecoal",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs_part2_foss(pe="pecoal",se="seel",te=tenoccs,vm_prodSe,pe2se,p_dataeta,vm_costfu_ex,vm_fuelex,sm_tdptwyr2dpgj,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1+cost2, "Operational costs|Elec|Coal|w/o CCS (billion US$2005/yr)"))
cost1 <- op_costs(ei="pecoal",eo="seel",te=teccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs_part2_foss(pe="pecoal",se="seel",te=teccs,vm_prodSe,pe2se,p_dataeta,vm_costfu_ex,vm_fuelex,sm_tdptwyr2dpgj,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1+cost2, "Operational costs|Elec|Coal|w/ CCS (billion US$2005/yr)"))
cost1 <- op_costs(ei="pegas",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs_part2_foss(pe="pegas",se="seel",te=tenoccs,vm_prodSe,pe2se,p_dataeta,vm_costfu_ex,vm_fuelex,sm_tdptwyr2dpgj,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1+cost2, "Operational costs|Elec|Gas|w/o CCS (billion US$2005/yr)"))
cost1 <- op_costs(ei="pegas",eo="seel",te=teccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs_part2_foss(pe="pegas",se="seel",te=teccs,vm_prodSe,pe2se,p_dataeta,vm_costfu_ex,vm_fuelex,sm_tdptwyr2dpgj,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1+cost2, "Operational costs|Elec|Gas|w/ CCS (billion US$2005/yr)"))
##### Biomass
price_pebiolc <- pebal.m[,,"pebiolc"] / (budget.m+1e-10) * 1000 / pm_conv_TWa_EJ
cost1 <- op_costs(ei="pebiolc",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- price_pebiolc * op_costs_part2_bio_nuc(pe="pebiolc",se="seel",te=tenoccs,vm_prodSe,pe2se,p_dataeta,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1+cost2, "Operational costs|Elec|Biomass|w/o CCS (billion US$2005/yr)"))
cost1 <- op_costs(ei="pebiolc",eo="seel",te=teccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- price_pebiolc * op_costs_part2_bio_nuc(pe="pebiolc",se="seel",te=teccs,vm_prodSe,pe2se,p_dataeta,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1+cost2, "Operational costs|Elec|Biomass|w/ CCS (billion US$2005/yr)"))
##### Nuclear
cost1 <- op_costs(ei="peur",eo="seel",te="tnrs",e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs_part2_bio_nuc(pe="peur",se="seel",te="tnrs",vm_prodSe,pe2se,p_dataeta,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1*cost2, "Operational costs|Elec|Nuclear (billion US$2005/yr)"))
##### Renewables
cost1 <- op_costs(ei=setdiff(perenew,pebio),eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost1, "Operational costs|Elec|Non-Bio Re (billion US$2005/yr)"))
cost1 <- op_costs(ei="pesol",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost1, "Operational costs|Elec|Solar (billion US$2005/yr)"))
cost1 <- op_costs(ei="pewin",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost1, "Operational costs|Elec|wind (billion US$2005/yr)"))
# add global values
tmp <- mbind(tmp, dimSums(tmp,dim=1))
# add other region aggregations
if (!is.null(regionSubsetList))
tmp <- mbind(tmp, calc_regionSubset_sums(tmp, regionSubsetList))
return(tmp)
}
pik-piam/remind documentation built on Sept. 9, 2021, 1:09 p.m.
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Defines functions reportCosts
Documented in reportCosts
#' Read in GDX and calculate costs, used in convGDX2MIF.R for the reporting
#'
#' Read in cost information from GDX file, information used in convGDX2MIF.R
#' for the reporting
#'
#'
#' @param gdx a GDX object as created by readGDX, or the path to a gdx
#' @param output a magpie object containing all needed variables generated by other report*.R functions
#' @param regionSubsetList a list containing regions to create report variables region
#' aggregations. If NULL (default value) only the global region aggregation "GLO" will
#' be created.
#' @return MAgPIE object - contains the cost variables
#' @author David Klein
#' @seealso \code{\link{convGDX2MIF}}
#' @examples
#'
#' \dontrun{reportCosts(gdx)}
#'
#' @export
#' @importFrom rlang .data
#' @importFrom magclass mbind getYears collapseNames dimSums setNames
#' @importFrom gdx readGDX
#' @importFrom dplyr filter
reportCosts <- function(gdx,output=NULL,regionSubsetList=NULL) {
# Cost calculation requires information from other reportings
if(is.null(output)){
cat("Executing reportExtraction\n")
output <- mbind(output,reportExtraction(gdx,regionSubsetList))
cat("Executing reportPrices\n")
output <- mbind(output,reportPrices(gdx,regionSubsetList=regionSubsetList))
cat("Executing reportEnergyInvestments\n")
output <- mbind(output,reportEnergyInvestment(gdx,regionSubsetList)[,getYears(output),])
}
########################################################################################
############# R E A D I N G I N P U T ###############################################
########################################################################################
# module realisations
module2realisation <- readGDX(gdx, "module2realisation", react = "silent")
industry_module <- module2realisation['industry' == module2realisation$modules, 2]
# Mappings
ccs2te <- readGDX(gdx,"ccs2te")
enty2rlf <- readGDX(gdx,c("pe2rlf","enty2rlf"),format="first_found")
teall2rlf <- readGDX(gdx,c("te2rlf","teall2rlf"),format="first_found")
pe2se <- readGDX(gdx,"pe2se")
se2fe <- readGDX(gdx,"se2fe")
se2se <- readGDX(gdx,c("se2se"),format="first_found")
# Sets
tenoccs <- readGDX(gdx,c("teNoCCS","tenoccs"),format="first_found")
temapall <- readGDX(gdx,c("en2en","temapall"),format="first_found")
tenotransform<- readGDX(gdx,c("teNoTransform","tenotransform"),format="first_found")
stor <- readGDX(gdx,c("teStor","stor"),format="first_found")
grid <- readGDX(gdx,c("teGrid","grid"),format="first_found")
trade_pe <- readGDX(gdx,c("tradePe","trade_pe"),format="first_found")
perenew <- readGDX(gdx,c("peRe","perenew"),format="first_found")
petyf <- readGDX(gdx,c("peFos","petyf"),format="first_found")
sety <- readGDX(gdx,c("entySe","sety"),format="first_found")
fety <- readGDX(gdx,c("entyFe","fety"),format="first_found")
potentialseLiq <- c("seliq","sepet","sedie") # the sety liquids changed from sepet+sedie to seLiq in REMIND 1.7
se_Liq <- intersect(potentialseLiq,sety)
teccs <- readGDX(gdx,c("teCCS","teccs"),format="first_found")
pebio <- readGDX(gdx,c("peBio","pebio"),format="first_found")
ppfen_stat <- readGDX(gdx,c("ppfen_stationary_dyn38","ppfen_stationary_dyn28","ppfen_stationary"),format="first_found", react = "silent")
if (length(ppfen_stat) == 0) ppfen_stat = NULL
fe2ppfen37 <- readGDX(gdx, 'fe2ppfen37', react = 'silent')
emiMacMagpie <- readGDX(gdx,c("emiMacMagpie"),format="first_found")
emiMacMagpieN2O <- readGDX(gdx,c("emiMacMagpieN2O"),format="first_found")
emiMacMagpieCH4 <- readGDX(gdx,c("emiMacMagpieCH4"),format="first_found")
emiMacMagpieCO2 <- readGDX(gdx,c("emiMacMagpieCO2"),format="first_found")
# Parameters
pm_conv_TWa_EJ <- 31.536
sm_tdptwyr2dpgj <- 31.71 #TerraDollar per TWyear to Dollar per
pm_data <- readGDX(gdx,name="pm_data",format="first_found")
pm_petradecost2_Mp_fin <- readGDX(gdx,name="pm_petradecost2_Mp_fin",format="first_found", react = "silent")
if(is.null(pm_petradecost2_Mp_fin)){
pm_petradecost2_Mp_fin <- readGDX(gdx,name="pm_costsTradePeFinancial",format="first_found")
pm_petradecost2_Mp_fin <- collapseNames(pm_petradecost2_Mp_fin[,,"Mport"])
}
p_dataeta <- readGDX(gdx,name=c("pm_dataeta","p_dataeta"),format="first_found")
pm_pvp <- readGDX(gdx,name=c("pm_pvp"),format = "first_found")
cost_emu_pre <- readGDX(gdx,name="p30_pebiolc_costs_emu_preloop",format="first_found")
cost_mag <- readGDX(gdx,name="p30_pebiolc_costsmag",format="first_found")[,getYears(cost_emu_pre),]
totLUcosts <- readGDX(gdx,name=c("pm_totLUcosts"),format="first_found")[,getYears(cost_emu_pre),]
totLUcostsWithMAC <- readGDX(gdx,name=c("p26_totLUcosts_withMAC"),format="first_found")[,getYears(cost_emu_pre),]
costsLuMACLookup <- readGDX(gdx,name=c("p26_macCostLu"),format="first_found")[,getYears(cost_emu_pre),]
costsMAC <- readGDX(gdx,name=c("pm_macCost","p_macCost"),format="first_found")[,getYears(cost_emu_pre),]
p_eta_conv <- readGDX(gdx,name=c("pm_eta_conv","p_eta_conv"),format = "first_found")
# Variables
Xport <- readGDX(gdx,name=c("vm_Xport"), field = "l",format = "first_found")
Mport <- readGDX(gdx,name=c("vm_Mport"), field = "l",format = "first_found")
vm_fuelex <- readGDX(gdx,name=c("vm_fuExtr","vm_fuelex"), field="l",restore_zeros=FALSE,format="first_found")[enty2rlf]
vm_costfu_ex <- readGDX(gdx,name=c("vm_costFuEx","vm_costfu_ex"), field="l",restore_zeros=FALSE,format="first_found")
v_costfu <- readGDX(gdx,name=c("v_costFu","v_costfu"), field="l",restore_zeros=FALSE,format="first_found")
v_costom <- readGDX(gdx,name=c("v_costOM","v_costom"), field="l", format="first_found")
v_costin <- readGDX(gdx,name=c("v_costInv","v_costin"), field = "l",format = "first_found")
vm_omcosts_cdr <- readGDX(gdx,name=c("vm_omcosts_cdr"), field="l", format="first_found")
vm_otherFEdemand <- readGDX(gdx,name=c("vm_otherFEdemand"), field="l",restore_zeros=FALSE,format="first_found")
v_investcost <- readGDX(gdx,name=c("vm_costTeCapital","v_costTeCapital","v_investcost"), field="l",format="first_found")
vm_cap <- readGDX(gdx,name=c("vm_cap"), field="l",format="first_found")
vm_cap[is.na(vm_cap)] <- 0
vm_prodSe <- readGDX(gdx,name=c("vm_prodSe"), field="l",restore_zeros=FALSE,format="first_found")
vm_prodFe <- readGDX(gdx,name=c("vm_prodFe"), field="l",restore_zeros=FALSE,format="first_found")
cost_emu <- readGDX(gdx,name=c("v30_pebiolc_costs"),field="l",format="first_found")
bio_cost_adjfac <- readGDX(gdx,name=c("v30_multcost"),field="l",format="first_found")
vm_cesIO <- readGDX(gdx, name = c('vm_cesIO'), field = 'l',
restore_zeros = FALSE)
# Equations
finenbal <- readGDX(gdx,name=c("fe2ppfEn","finenbal"), types="sets",format="first_found")
pebal.m <- readGDX(gdx,name=c("q_balPe","qm_pebal"), types="equations",field="m",format="first_found")
budget.m <- readGDX(gdx,name='qm_budget', types="equations",field="m",format="first_found") # alternative: calcPrice
sebal.m <- readGDX(gdx,name=c("q_balSe","q_sebal"), types="equations",field="m",format="first_found")
febal.m <- readGDX(gdx,name=c("q_balFe","q_febal"), types="equations",field="m",format="first_found")[,,fety]
balfinen.m <- readGDX(gdx,name=c("qm_balFeForCesAndEs","qm_balFeForCes","q_balFeForCes","q_balfinen"),types="equations",field="m",format="first_found")[finenbal]
# Find common years
y <- Reduce(intersect,list(getYears(vm_fuelex),
getYears(vm_costfu_ex),
getYears(p_dataeta),
getYears(v_investcost),
getYears(vm_cap),
getYears(vm_prodSe)))
# Reduce to common years
p_dataeta <- p_dataeta[,y,]
pm_pvp <- pm_pvp[,y,]
vm_fuelex <- vm_fuelex[,y,]
Xport <- Xport[,y,]
Mport <- Mport[,y,]
vm_costfu_ex <- vm_costfu_ex[,y,]
v_costfu <- v_costfu[,y,]
v_costom <- v_costom[,y,]
v_costin <- v_costin[,y,]
vm_otherFEdemand <- vm_otherFEdemand[,y,]
v_investcost <- v_investcost[,y,]
vm_cap <- vm_cap[,y,]
vm_prodSe <- vm_prodSe[,y,]
pebal.m <- pebal.m[,y,]
budget.m <- budget.m[,y,]
sebal.m <- sebal.m[,y,]
febal.m <- febal.m[,y,]
balfinen.m <- balfinen.m[,y,]
vm_omcosts_cdr <- vm_omcosts_cdr[,y,]
output <- output[,y,]
p_eta_conv <- p_eta_conv[,y,]
# Gather efficiency data in only one magpie object to enable generic structure of below defined functions:
# Take values from pm_data (constant efficiency over time) for technologies where p_dataeta (time variant efficiencies) has no values.
# Thus, in the below defined formulas time variant efficiencies will be used if available otherwise time invariant
for (te in magclass::getNames(p_dataeta)) {
if(all(p_dataeta[,,te]==0)) {
for (year in getYears(p_dataeta)) {
p_dataeta[,year,te] <- pm_data[,,"eta"][,,te]
}
}
}
########################################################################################
############# F U N C T I O N S D E F I N I T I O N #################################
########################################################################################
op_costs_part2_foss <- function(pe,se,te,vm_prodSe,i_pe2se,p_dataeta,vm_costfu_ex,vm_fuelex,sm_tdptwyr2dpgj,pm_conv_TWa_EJ) {
sub_pe2se <- i_pe2se[(pe2se$all_enty %in% pe) & (i_pe2se$all_enty1 %in% se) & (i_pe2se$all_te %in% te),]
out <- dimSums( vm_costfu_ex[,,pe] / dimSums(vm_fuelex[,,pe],dim = 3, na.rm = T), dim = 3, na.rm = T) * sm_tdptwyr2dpgj * # Average supply costs
dimSums( vm_prodSe[sub_pe2se] / p_dataeta[,,sub_pe2se$all_te], dim = 3, na.rm = T) * pm_conv_TWa_EJ
return(out)
}
op_costs_part2_bio_nuc <- function(pe,se,te,vm_prodSe,i_pe2se,p_dataeta,pm_conv_TWa_EJ) {
sub_pe2se <- i_pe2se[(pe2se$all_enty %in% pe) & (i_pe2se$all_enty1 %in% se) & (i_pe2se$all_te %in% te),]
out <- dimSums( vm_prodSe[sub_pe2se] / p_dataeta[,,sub_pe2se$all_te], dim = 3, na.rm = T) * pm_conv_TWa_EJ
return(out)
}
# operation and maintenance costs
op_costs <- function(ei,eo,te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost) {
# Check whether a mapping with energy transfering technologies is given or just technologies
if (!is.null(e2e)) {
sub_e2e <- e2e[(e2e$all_enty %in% ei) & (e2e$all_enty1 %in% eo) & (e2e$all_te %in% te),]
# Save technologies to extra variables because in the "else" case there is no sub_e2e list that could be used
e2e_allte <- sub_e2e$all_te
} else {
e2e_allte <- te
}
vm_cap <- dimSums(vm_cap,dim=3.2,na.rm=T) # get rid of grades which are not used in calculations below because all other variables dont have them neither
out <- dimSums( # sum OMF over technologies
collapseNames(pm_data[,,"omf"])[,,e2e_allte] *
(dimSums((v_investcost[,,e2e_allte] * vm_cap[,,e2e_allte])[teall2rlf],dim=3.2,na.rm=T) # sum over rlf
)[,, e2e_allte],dim = 3, na.rm = T)
if(!is.null(vm_prodE) & !length(e2e_allte)==0) { # if either SE or FE is produced, then variable O&M is added
out <- out + dimSums(collapseNames(pm_data[,,"omv"])[,,sub_e2e$all_te] * dimSums(vm_prodE[sub_e2e],dim=c(3.1,3.2),na.rm=T)
, dim = 3, na.rm = T)
}
out <- out * 1000
return(out)
}
cost_Mport <- function(pety,pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport) {
out <- dimSums((pm_petradecost2_Mp_fin[,,pety] + (pm_pvp[,,pety] / (budget.m + 1.e-10))) * Mport[,,pety], dim = 3, na.rm = T) * 1000
return(out)
}
########################################################################################
############# O U T P U T G E N E R A T I O N ########################################
########################################################################################
# Initialize empty object that will be filled with reporting results
tmp <- NULL
# Calculate and append new variables to magpie object
#######################################
########## Biomass costs ##############
#######################################
if(!is.null(cost_mag)) {tmp <- mbind(tmp,setNames(cost_mag * 1000, "Costs|Biomass|MAgPIE (billion US$2005/yr)"))}
tmp <- mbind(tmp,setNames(cost_emu_pre * 1000, "Costs|Biomass|Price integral presolve (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(cost_emu * 1000, "Costs|Biomass|Price integral (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(bio_cost_adjfac, "Costs|Biomass|Adjfactor (-)"))
if(!is.null(totLUcosts)) {tmp <- mbind(tmp,setNames(totLUcosts * 1000, "Costs|Land Use (billion US$2005/yr)"))}
if(!is.null(totLUcostsWithMAC)) {tmp <- mbind(tmp,setNames(totLUcostsWithMAC * 1000, "Costs|Land Use with MAC-costs from MAgPIE (billion US$2005/yr)"))}
if(!is.null(costsLuMACLookup)) {tmp <- mbind(tmp,setNames(costsLuMACLookup * 1000, "Costs|Land Use|MAC-costs Lookup (billion US$2005/yr)"))}
if(!is.null(getNames(costsMAC))) tmp <- mbind(tmp,setNames(dimSums(costsMAC[,,emiMacMagpie], dim = 3, na.rm = T) * 1000, "Costs|Land Use|MAC-costs (billion US$2005/yr)"))
if(!is.null(getNames(costsMAC))) tmp <- mbind(tmp,setNames(dimSums(costsMAC[,,emiMacMagpieN2O],dim = 3, na.rm = T) * 1000, "Costs|Land Use|MAC-costs|N2O (billion US$2005/yr)"))
if(!is.null(getNames(costsMAC))) tmp <- mbind(tmp,setNames(dimSums(costsMAC[,,emiMacMagpieCH4],dim = 3, na.rm = T) * 1000, "Costs|Land Use|MAC-costs|CH4 (billion US$2005/yr)"))
if(!is.null(getNames(costsMAC))) tmp <- mbind(tmp,setNames(dimSums(costsMAC[,,emiMacMagpieCO2],dim = 3, na.rm = T) * 1000, "Costs|Land Use|MAC-costs|CO2 (billion US$2005/yr)"))
tmp <- tmp[,y,]
#######################################
########## Fuel Costs #################
#######################################
##### Total
tmp <- mbind(tmp,setNames(v_costfu * 1000, "Fuel supply costs (billion US$2005/yr)"))
##### Fuel costs for own ESM
regi_on_gdx <- unique(readGDX(gdx, name = "regi2iso")[,1])
# v_costfu: these costs are the total fuel extraction costs, even the ones for export
# Supply costs: exports valued at supply cost (else the ESM costs would be greatly underestimated for a resource-exporting country that makes large profits from the export), except for biomass where supply costs are not yet reported
cost <- v_costfu * 1000 - setNames(output[regi_on_gdx,,"Res|Average Supply Costs|Coal ($/GJ)"] * Xport[,,"pecoal"] * pm_conv_TWa_EJ,NULL) -
setNames(output[regi_on_gdx,,"Res|Average Supply Costs|Gas ($/GJ)"] * Xport[,,"pegas"] * pm_conv_TWa_EJ,NULL) -
setNames(output[regi_on_gdx,,"Res|Average Supply Costs|Oil ($/GJ)"] * Xport[,,"peoil"] * pm_conv_TWa_EJ,NULL) -
setNames(output[regi_on_gdx,,"Price|Biomass|Primary Level (US$2005/GJ)"] * Xport[,,"pebiolc"] * pm_conv_TWa_EJ,NULL) -
setNames(output[regi_on_gdx,,"Res|Average Supply Costs|Uranium ($/GJ)"] * Xport[,,"peur"] * pm_conv_TWa_EJ * 4.43,NULL) +
dimSums(Mport[,,trade_pe] * pebal.m[,,trade_pe] / (budget.m + 1.e-10), dim = 3, na.rm = T) * 1000 # imports valued with domestic market price
tmp <- mbind(tmp,setNames(cost, "Fuel costs for own ESM (billion US$2005/yr)"))
##### Import fuel costs
cost<- cost_Mport(trade_pe,pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport)
tmp <- mbind(tmp,setNames(cost, "Import Fuel costs (billion US$2005/yr)"))
###### Import fuel costs|Coal
cost<- cost_Mport("pecoal",pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport)
tmp <- mbind(tmp,setNames(cost, "Import Fuel costs|Coal (billion US$2005/yr)"))
###### Import fuel costs|Gas
cost<- cost_Mport("pegas",pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport)
tmp <- mbind(tmp,setNames(cost, "Import Fuel costs|Gas (billion US$2005/yr)"))
###### Import fuel costs|Oil
cost<- cost_Mport("peoil",pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport)
tmp <- mbind(tmp,setNames(cost, "Import Fuel costs|Oil (billion US$2005/yr)"))
###### Import fuel costs|Uranium
cost<- cost_Mport("peur",pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport)
tmp <- mbind(tmp,setNames(cost, "Import Fuel costs|Uranium (billion US$2005/yr)"))
###### Import fuel costs|Pebiolc
cost<- cost_Mport("pebiolc",pm_petradecost2_Mp_fin,pm_pvp,budget.m,Mport)
tmp <- mbind(tmp,setNames(cost, "Import Fuel costs|Biomass (billion US$2005/yr)"))
###### Export Fuel Costs|Coal
cost <- output[regi_on_gdx,,"Res|Average Supply Costs|Coal ($/GJ)"] * Xport[,,"pecoal"] * pm_conv_TWa_EJ
tmp <- mbind(tmp,setNames(cost, "Export Fuel costs|Coal (billion US$2005/yr)"))
###### Export Fuel Costs|Gas
cost <- output[regi_on_gdx,,"Res|Average Supply Costs|Gas ($/GJ)"] * Xport[,,"pegas"] * pm_conv_TWa_EJ
tmp <- mbind(tmp,setNames(cost, "Export Fuel costs|Gas (billion US$2005/yr)"))
###### Export Fuel Costs|Oil
cost <- output[regi_on_gdx,,"Res|Average Supply Costs|Oil ($/GJ)"] * Xport[,,"peoil"] * pm_conv_TWa_EJ
tmp <- mbind(tmp,setNames(cost, "Export Fuel costs|Oil (billion US$2005/yr)"))
###### Export Fuel Costs|Biomass
#cost <- output[regi_on_gdx,,"Res|Average Supply Costs|Biomass ($/GJ)"] * Xport[,,"pebiolc"]
#tmp <- mbind(tmp,setNames(cost, "Export Fuel costs|Biomass (billion US$2005/yr)"))
###### Export Fuel Costs|Uranium
cost <- output[regi_on_gdx,,"Res|Average Supply Costs|Uranium ($/GJ)"] * Xport[,,"peur"] * p_eta_conv[,,"tnrs"] * pm_conv_TWa_EJ
tmp <- mbind(tmp,setNames(cost, "Export Fuel costs|Uranium (billion US$2005/yr)"))
#######################################
########## Energy System costs ########
#######################################
cost <- (v_costin + v_costom) * 1000 + tmp[,,"Fuel costs for own ESM (billion US$2005/yr)"]
tmp <- mbind(tmp,setNames(cost,"Energy system costs (billion US$2005/yr)"))
#######################################
########## Energy costs ###############
#######################################
if (!is.null(ppfen_stat)){
##### CDR
price_feels <- abs(balfinen.m[,,"feels.feels"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Electricity|Stationary (US$2005/GJ)")
price_fedie <- abs(febal.m[,,"fedie"] /(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Diesel (US$2005/GJ)")
price_fehes <- abs(balfinen.m[,,"fehes.fehes"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Heat|
price_fegas <- abs(balfinen.m[,,"fegas.fegas"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Gas (US$2005/GJ)")
price_feh2s <- abs(balfinen.m[,,"feh2s.feh2s"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Hydrogen|Stationary (US$2005/GJ)")
# reduce names in 3rd dimension
price_feels <- setNames(price_feels,"feels") # reduce feels.feels to feels
price_fehes <- setNames(price_fehes,"fehes") # reduce fehes.fehes to fehes
price_fegas <- setNames(price_fegas,"fegas") # reduce fegas.fegas to fegas
price_feh2s <- setNames(price_feh2s,"feh2s") # reduce feh2s.feh2s to feh2s
tmp <- mbind(tmp,setNames(price_feels * vm_otherFEdemand[,,"feels"] * pm_conv_TWa_EJ, "Energy costs CDR|Electricity (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(price_fedie * vm_otherFEdemand[,,"fedie"] * pm_conv_TWa_EJ, "Energy costs CDR|Diesel (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames((price_fegas * vm_otherFEdemand[,,"fegas"] + price_feh2s * vm_otherFEdemand[,,"feh2s"]) * pm_conv_TWa_EJ, "Energy costs CDR|Heat (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(price_feels * vm_otherFEdemand[,,"feels"] * pm_conv_TWa_EJ +
price_fedie * vm_otherFEdemand[,,"fedie"] * pm_conv_TWa_EJ +
price_fehes * vm_otherFEdemand[,,"fehes"] * pm_conv_TWa_EJ,
"Energy costs CDR (billion US$2005/yr)"))
} else {
if ('subsectors' == industry_module) {
fe2ppfen37_feels <- filter(fe2ppfen37, 'feels' == .data$all_enty)
fe2ppfen37_fegas <- filter(fe2ppfen37, 'fegas' == .data$all_enty)
fe2ppfen37_feh2s <- filter(fe2ppfen37, 'feh2s' == .data$all_enty)
# "Price|Final Energy|Electricity|Industry (US$2005/GJ)")
price_feeli <- abs(
( dimSums(
mselect(balfinen.m, fe2ppfen37_feels)
* vm_cesIO[,y,fe2ppfen37_feels$all_in],
dim = 3, na.rm = T)
/ dimSums(vm_cesIO[,y,fe2ppfen37_feels$all_in], dim = 3, na.rm = T)
)
/ (budget.m + 1e-10) * 1000 / pm_conv_TWa_EJ
)
# "Price|Final Energy|Gases|Industry (US$2005/GJ)")
price_fegai <- abs(
( dimSums(
mselect(balfinen.m, fe2ppfen37_fegas)
* vm_cesIO[,y,fe2ppfen37_fegas$all_in],
dim = 3, na.rm = T)
/ dimSums(vm_cesIO[,y,fe2ppfen37_fegas$all_in], dim = 3, na.rm = T)
)
/ (budget.m + 1e-10) * 1000 / pm_conv_TWa_EJ
)
# "Price|Final Energy|Hydrogen|Industry (US$2005/GJ)")
price_feh2i <- abs(
( dimSums(
mselect(balfinen.m, fe2ppfen37_feh2s)
* vm_cesIO[,y,fe2ppfen37_feh2s$all_in],
dim = 3, na.rm = T)
/ dimSums(vm_cesIO[,y,fe2ppfen37_feh2s$all_in], dim = 3, na.rm = T)
)
/ (budget.m + 1e-10) * 1000 / pm_conv_TWa_EJ
)
} else {
price_feeli <- abs(balfinen.m[,,"feels.feeli"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Electricity|Industry (US$2005/GJ)")
price_fegai <- abs(balfinen.m[,,"fegas.fegai"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Gases|Industry (US$2005/GJ)")
price_feh2i <- abs(balfinen.m[,,"feh2s.feh2i"]/(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Hydrogen|Industry (US$2005/GJ)")
}
price_fedie <- abs(febal.m[,,"fedie"] /(budget.m+1e-10)) * 1000 / pm_conv_TWa_EJ # "Price|Final Energy|Diesel (US$2005/GJ)")
# reduce names in 3rd dimension
price_feeli <- setNames(price_feeli,"feeli") # reduce feels.feels to feels
price_fegai <- setNames(price_fegai,"fegai") # reduce fehes.fehes to fehes
price_feh2i <- setNames(price_feh2i,"feh2i") # reduce fehes.fehes to fehes
tmp <- mbind(tmp,setNames(price_feeli * vm_otherFEdemand[,,"feels"] * pm_conv_TWa_EJ , "Energy costs CDR|Electricity (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(price_fedie * vm_otherFEdemand[,,"fedie"] * pm_conv_TWa_EJ, "Energy costs CDR|Diesel (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(price_fegai * vm_otherFEdemand[,,"fegas"] * pm_conv_TWa_EJ +
price_feh2i * vm_otherFEdemand[,,"feh2s"] * pm_conv_TWa_EJ, "Energy costs CDR|Heat (billion US$2005/yr)"))
tmp <- mbind(tmp,setNames(price_feeli * vm_otherFEdemand[,,"feels"] * pm_conv_TWa_EJ +
price_fedie * vm_otherFEdemand[,,"fedie"] * pm_conv_TWa_EJ +
price_fegai * vm_otherFEdemand[,,"fegas"] * pm_conv_TWa_EJ +
price_feh2i * vm_otherFEdemand[,,"feh2s"] * pm_conv_TWa_EJ,
"Energy costs CDR (billion US$2005/yr)"))
}
#######################################
########## Total Energy costs #########
#######################################
##### Total
cost1 <- op_costs(ei=temapall$all_enty,eo=sety,te=teall2rlf$all_te,e2e=temapall,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs(ei=temapall$all_enty,eo=fety,te=teall2rlf$all_te,e2e=temapall,teall2rlf=teall2rlf,vm_prodE=vm_prodFe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost3 <- op_costs(ei=NULL,eo=NULL,te=tenotransform,e2e=NULL,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost1 + cost2 + cost3 + output[regi_on_gdx,,"Energy Investments|Supply (billion US$2005/yr)"], "Total Energy costs (billion US$2005/yr)"))
##### Electricity
cost1 <- op_costs(ei=pe2se$all_enty,eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs(ei="seel",eo=se2fe$all_enty1,te=se2fe$all_te,e2e=se2fe,teall2rlf=teall2rlf,vm_prodE=vm_prodFe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost3 <- op_costs(ei=NULL,eo=NULL,te=tenotransform,e2e=NULL,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost1 + cost2 + cost3 + output[regi_on_gdx,,"Energy Investments|Electricity (billion US$2005/yr)"], "Total Energy costs|Electricity (billion US$2005/yr)"))
##### Elec|Fossil
cost <- op_costs(ei=petyf,eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Fossil (billion US$2005/yr)"], "Total Energy costs|Elec|Fossil (billion US$2005/yr)"))
##### Elec|Non-fossil
cost <- op_costs(ei=setdiff(pe2se$all_enty,petyf),eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Non-Fossil (billion US$2005/yr)"], "Total Energy costs|Elec|Non-Fossil (billion US$2005/yr)"))
##### Elec|Biomass
cost <- op_costs(ei="pebiolc",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Biomass (billion US$2005/yr)"], "Total Energy costs|Elec|Biomass (billion US$2005/yr)"))
cost <- op_costs(ei="pebiolc",eo="seel",te=teccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Biomass|w/ CCS (billion US$2005/yr)"], "Total Energy costs|Elec|Biomass|w/ CCS (billion US$2005/yr)"))
cost <- op_costs(ei="pebiolc",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Biomass|w/o CCS (billion US$2005/yr)"], "Total Energy costs|Elec|Biomass|w/o CCS (billion US$2005/yr)"))
##### Elec|Coal
cost <- op_costs(ei="pecoal",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost <- cost + output[regi_on_gdx,,"Energy Investments|Elec|Coal (billion US$2005/yr)"]
tmp <- mbind(tmp,setNames(cost, "Total Energy costs|Elec|Coal (billion US$2005/yr)"))
cost <- op_costs(ei="pecoal",eo="seel",te=teccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost <- cost + output[regi_on_gdx,,"Energy Investments|Elec|Coal|w/ CCS (billion US$2005/yr)"]
tmp <- mbind(tmp,setNames(cost, "Total Energy costs|Elec|Coal|w/ CCS (billion US$2005/yr)"))
cost <- op_costs(ei="pecoal",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost <- cost + output[regi_on_gdx,,"Energy Investments|Elec|Coal|w/o CCS (billion US$2005/yr)"]
tmp <- mbind(tmp,setNames(cost, "Total Energy costs|Elec|Coal|w/o CCS (billion US$2005/yr)"))
##### Elec|Gas
cost <- op_costs(ei="pegas",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Gas (billion US$2005/yr)"], "Total Energy costs|Elec|Gas (billion US$2005/yr)"))
cost <- op_costs(ei="pegas",eo="seel",te=teccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Gas|w/ CCS (billion US$2005/yr)"], "Total Energy costs|Elec|Gas|w/ CCS (billion US$2005/yr)"))
cost <- op_costs(ei="pegas",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Gas|w/o CCS (billion US$2005/yr)"], "Total Energy costs|Elec|Gas|w/o CCS (billion US$2005/yr)"))
##### Elec|Oil
cost <- op_costs(ei="peoil",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Oil (billion US$2005/yr)"], "Total Energy costs|Elec|Oil (billion US$2005/yr)"))
cost <- op_costs(ei="peoil",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Oil|w/o CCS (billion US$2005/yr)"], "Total Energy costs|Elec|Oil|w/o CCS (billion US$2005/yr)"))
##### Elec|Nuclear
cost <- op_costs(ei="peur",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Nuclear (billion US$2005/yr)"], "Total Energy costs|Elec|Nuclear (billion US$2005/yr)"))
##### Elec|Non-biomass renewables
cost <- op_costs(ei=setdiff(perenew,pebio),eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Non-Bio Re (billion US$2005/yr)"], "Total Energy costs|Elec|Non-Bio Re (billion US$2005/yr)"))
##### Elec|Solar
cost <- op_costs(ei="pesol",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Solar (billion US$2005/yr)"], "Total Energy costs|Elec|Solar (billion US$2005/yr)"))
##### Elec|Wind
cost <- op_costs(ei="pewin",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Wind (billion US$2005/yr)"], "Total Energy costs|Elec|Wind (billion US$2005/yr)"))
##### Elec|Hydro
cost <- op_costs(ei="pehyd",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Hydro (billion US$2005/yr)"], "Total Energy costs|Elec|Hydro (billion US$2005/yr)"))
##### Elec|Geothermal
cost <- op_costs(ei="pegeo",eo="seel",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Geothermal (billion US$2005/yr)"], "Total Energy costs|Elec|Geothermal (billion US$2005/yr)"))
##### Elec|Hydrogen
if ("h2turb" %in% se2se$all_te) {
cost <- op_costs(ei="seh2",eo="seel",te=se2se$all_te,e2e=se2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Hydrogen (billion US$2005/yr)"], "Total Energy costs|Elec|Hydrogen (billion US$2005/yr)"))
}
##### Elec|Storage
cost <- op_costs(ei=NULL,eo=NULL,te=stor,e2e=NULL,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Elec|Storage (billion US$2005/yr)"], "Total Energy costs|Elec|Storage (billion US$2005/yr)"))
##### Elec|Grid
cost1 <- op_costs(ei=NULL,eo=NULL,te=grid,e2e=NULL,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs(ei="seel",eo=se2fe$all_enty1,te=se2fe$all_te,e2e=se2fe,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost1 + cost2 + output[regi_on_gdx,,"Energy Investments|Elec|Grid (billion US$2005/yr)"], "Total Energy costs|Elec|Grid (billion US$2005/yr)"))
##### Heat
#TiA: including investments, and operation and maintenance, BUT excluding input fuel costs
cost_pe2se <- op_costs(ei=pe2se$all_enty,eo="sehe",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost_se2fe <- op_costs(ei="sehe",eo=se2fe$all_enty1,te=se2fe$all_te,e2e=se2fe,teall2rlf=teall2rlf,vm_prodE=vm_prodFe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost_pe2se + cost_se2fe + output[regi_on_gdx,,"Energy Investments|Heat (billion US$2005/yr)"], "Total Energy costs|Heat (billion US$2005/yr)"))
##### Hydrogen
#TiA: including investments, and operation and maintenance, BUT excluding input fuel costs
cost_pe2se <- op_costs(ei=pe2se$all_enty,eo="seh2",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost_se2fe <- op_costs(ei="seh2",eo=se2fe$all_enty1,te=se2fe$all_te,e2e=se2fe,teall2rlf=teall2rlf,vm_prodE=vm_prodFe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost_pe2se + cost_se2fe + output[regi_on_gdx,,"Energy Investments|Hydrogen (billion US$2005/yr)"], "Total Energy costs|Hydrogen (billion US$2005/yr)"))
##### Hydrogen|Fossil
cost <- op_costs(ei=petyf,eo="seh2",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Hydrogen|Fossil (billion US$2005/yr)"], "Total Energy costs|Hydrogen|Fossil (billion US$2005/yr)"))
##### Hydrogen|RE
cost <- op_costs(ei=perenew,eo="seh2",te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Hydrogen|RE (billion US$2005/yr)"], "Total Energy costs|Hydrogen|RE (billion US$2005/yr)"))
##### Liquids
#TiA: including investments, and operation and maintenance, BUT excluding input fuel costs
cost_pe2se <- op_costs(ei=pe2se$all_enty,eo=se_Liq,te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost_se2fe <- op_costs(ei=se_Liq,eo=se2fe$all_enty1,te=se2fe$all_te,e2e=se2fe,teall2rlf=teall2rlf,vm_prodE=vm_prodFe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost_pe2se + cost_se2fe + output[regi_on_gdx,,"Energy Investments|Liquids (billion US$2005/yr)"], "Total Energy costs|Liquids (billion US$2005/yr)"))
##### Liquids|Oil Ref
cost <- op_costs(ei="peoil",eo=se_Liq,te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Liquids|Oil Ref (billion US$2005/yr)"], "Total Energy costs|Liquids|Oil Ref (billion US$2005/yr)"))
##### Liquids|Fossil|w/ oil
cost <- op_costs(ei=petyf,eo=se_Liq,te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Liquids|Fossil|w/ oil (billion US$2005/yr)"], "Total Energy costs|Liquids|Fossil|w/ oil (billion US$2005/yr)"))
##### Liquids|Fossil
cost <- op_costs(ei="pecoal",eo=se_Liq,te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Liquids|Fossil (billion US$2005/yr)"], "Total Energy costs|Liquids|Fossil (billion US$2005/yr)"))
##### Liquids|Bio
cost <- op_costs(ei=perenew,eo=se_Liq,te=pe2se$all_te,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|Liquids|Bio (billion US$2005/yr)"], "Total Energy costs|Liquids|Bio (billion US$2005/yr)"))
##### CO2 Trans&Stor
cost <- op_costs(ei=ccs2te$all_enty,eo=ccs2te$all_enty1,te=ccs2te$all_te,e2e=ccs2te,teall2rlf=teall2rlf,vm_prodE=NULL,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost + output[regi_on_gdx,,"Energy Investments|CO2 Trans&Stor (billion US$2005/yr)"], "Total Energy costs|CO2 Trans&Stor (billion US$2005/yr)"))
##### Other
tmp <- mbind(tmp,setNames(tmp[,,"Total Energy costs (billion US$2005/yr)"]-
tmp[,,"Total Energy costs|Electricity (billion US$2005/yr)"]-
tmp[,,"Total Energy costs|Hydrogen (billion US$2005/yr)"]-
tmp[,,"Total Energy costs|Liquids (billion US$2005/yr)"]-
tmp[,,"Total Energy costs|Heat (billion US$2005/yr)"]-
tmp[,,"Total Energy costs|CO2 Trans&Stor (billion US$2005/yr)"],
"Total Energy costs|Other (billion US$2005/yr)"))
#####################################
########## O & M costs ##############
#####################################
ei=temapall$all_enty
eo=sety
te=teall2rlf$all_te
e2e=temapall
##### Total
tmp <- mbind(tmp,setNames(v_costom * 1000, "OandM costs (billion US$2005/yr)"))
##### CDR
tmp <- mbind(tmp,setNames(vm_omcosts_cdr * 1000, "OandM costs CDR (billion US$2005/yr)"))
#####################################
########## Operational costs ########
#####################################
##### Fossils
cost1 <- op_costs(ei="pecoal",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs_part2_foss(pe="pecoal",se="seel",te=tenoccs,vm_prodSe,pe2se,p_dataeta,vm_costfu_ex,vm_fuelex,sm_tdptwyr2dpgj,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1+cost2, "Operational costs|Elec|Coal|w/o CCS (billion US$2005/yr)"))
cost1 <- op_costs(ei="pecoal",eo="seel",te=teccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs_part2_foss(pe="pecoal",se="seel",te=teccs,vm_prodSe,pe2se,p_dataeta,vm_costfu_ex,vm_fuelex,sm_tdptwyr2dpgj,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1+cost2, "Operational costs|Elec|Coal|w/ CCS (billion US$2005/yr)"))
cost1 <- op_costs(ei="pegas",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs_part2_foss(pe="pegas",se="seel",te=tenoccs,vm_prodSe,pe2se,p_dataeta,vm_costfu_ex,vm_fuelex,sm_tdptwyr2dpgj,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1+cost2, "Operational costs|Elec|Gas|w/o CCS (billion US$2005/yr)"))
cost1 <- op_costs(ei="pegas",eo="seel",te=teccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs_part2_foss(pe="pegas",se="seel",te=teccs,vm_prodSe,pe2se,p_dataeta,vm_costfu_ex,vm_fuelex,sm_tdptwyr2dpgj,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1+cost2, "Operational costs|Elec|Gas|w/ CCS (billion US$2005/yr)"))
##### Biomass
price_pebiolc <- pebal.m[,,"pebiolc"] / (budget.m+1e-10) * 1000 / pm_conv_TWa_EJ
cost1 <- op_costs(ei="pebiolc",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- price_pebiolc * op_costs_part2_bio_nuc(pe="pebiolc",se="seel",te=tenoccs,vm_prodSe,pe2se,p_dataeta,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1+cost2, "Operational costs|Elec|Biomass|w/o CCS (billion US$2005/yr)"))
cost1 <- op_costs(ei="pebiolc",eo="seel",te=teccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- price_pebiolc * op_costs_part2_bio_nuc(pe="pebiolc",se="seel",te=teccs,vm_prodSe,pe2se,p_dataeta,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1+cost2, "Operational costs|Elec|Biomass|w/ CCS (billion US$2005/yr)"))
##### Nuclear
cost1 <- op_costs(ei="peur",eo="seel",te="tnrs",e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
cost2 <- op_costs_part2_bio_nuc(pe="peur",se="seel",te="tnrs",vm_prodSe,pe2se,p_dataeta,pm_conv_TWa_EJ)
tmp <- mbind(tmp,setNames(cost1*cost2, "Operational costs|Elec|Nuclear (billion US$2005/yr)"))
##### Renewables
cost1 <- op_costs(ei=setdiff(perenew,pebio),eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost1, "Operational costs|Elec|Non-Bio Re (billion US$2005/yr)"))
cost1 <- op_costs(ei="pesol",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost1, "Operational costs|Elec|Solar (billion US$2005/yr)"))
cost1 <- op_costs(ei="pewin",eo="seel",te=tenoccs,e2e=pe2se,teall2rlf=teall2rlf,vm_prodE=vm_prodSe,pm_data=pm_data,vm_cap=vm_cap,v_investcost=v_investcost)
tmp <- mbind(tmp,setNames(cost1, "Operational costs|Elec|wind (billion US$2005/yr)"))
# add global values
tmp <- mbind(tmp, dimSums(tmp,dim=1))
# add other region aggregations
if (!is.null(regionSubsetList))
tmp <- mbind(tmp, calc_regionSubset_sums(tmp, regionSubsetList))
return(tmp)
}
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