R/reportExchange.R
In pik-piam/limes: The liMES R package
Defines functions
reportExchange
Documented in
reportExchange
#' Read in GDX and calculate electricity exchange, value of exchange and aggregated transmission capacites, used in convGDX2MIF.R for the reporting
#'
#' Read in electricity exchange data 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
#' @return MAgPIE object - contains the capacity variables
#' @author Sebastian Osorio, Renato Rodrigues
#' @seealso \code{\link{convGDX2MIF}}
#' @examples
#'
#' \dontrun{reportExchange(gdx)}
#'
#' @importFrom gdx readGDX
#' @importFrom magclass mbind setNames dimSums getSets getSets<- as.magpie getNames<- getItems<- getItems
#' @export
#'
reportExchange <- function(gdx) {
# read parameters and sets
trans <- readGDX(gdx, name = "trans") #set of cross-border transmission lines (numeric)
tau <- readGDX(gdx, name = "tau") #set of tau
regi <- readGDX(gdx, name = "regi") #set of countries
tt <- readGDX(gdx, name = "t") #set of time
tt <- readGDX(gdx, name = "t", field = "l", format = "first_found") # time set
t0 <- tt[1]
c_esmdisrate <- readGDX(gdx, name = "c_esmdisrate", field = "l", format = "first_found") #interest rate
p_tedataconn <- readGDX(gdx, name = "p_tedataconn", field = "l", format = "first_found") #technical parameters of transmission
p_ts <- readGDX(gdx, name = "p_ts", field = "l", format = "first_found") #time step
p_taulength <- readGDX(gdx, name = c("p_taulength", "pm_taulength"), field = "l", format = "first_found")[, , tau] #number of hours/year per tau
# read variables
v_transflow1 <- readGDX(gdx, name = "v_transflow1", field = "l", format = "first_found")
v_transflow2 <- readGDX(gdx, name = "v_transflow2", field = "l", format = "first_found")
v_captrans <- readGDX(gdx, name = "v_captrans", field = "l", format = "first_found")
#define the losses
p_losses <- p_tedataconn[, , "loss"]
p_length <- p_tedataconn[, , "length"]
#ELECTRICITY PRICES (needed for computing import and export prices)
# read variables
m_elecprices <- readGDX(gdx, name = "q_sebal", field = "m", format = "first_found")
m_elecprices <- m_elecprices[, , "seel"]
# create MagPie object of m_elecprices with iso3 regions
m_elecprices <- limesMapping(m_elecprices)[, , tau]
# calculate marginal value per tau
m_elecprices = m_elecprices/p_taulength
#compute factor to discount average marginal values
f_npv <- as.numeric(p_ts)*exp(-as.numeric(c_esmdisrate)*(as.numeric(tt)-as.numeric(t0)))
#discounting marginal values [Geur/GWh]
m_elecprices_tmp <- NULL
for (t2 in 1:length(tt)) {
m_elecprices_tmp <- mbind(m_elecprices_tmp, m_elecprices[, t2, ]/f_npv[t2])
}
# settings mapping path
mappingPath <- system.file("extdata", "LIMES_country_ISO_3.csv", package = "limes")
# reading mapping file
mapping <- read.csv(mappingPath, sep = ";")
#Create variables for NET EXPORTS of the same size and forman than v_transflow
v_netflow1 <- v_transflow1*0
v_netflow2 <- v_transflow2*0
#----------------------------------------------------------------------------------
#EXPORTS
exports <- NULL
capexports <- NULL
valueexports <- NULL
expo_regi <- NULL
netexpo_regi <- NULL
cap_regi <- NULL
#estimate aggregated (total) exports from each country
for (regi2 in regi) {
#initialize variables to aggregate positive flows
partMagPie1<-0
cap1<-0
value1 <- 0
expo1 <- NULL
netexpo1 <- NULL
cap_regi1 <- NULL
#aggregate the positive flows
conns1 <- trans[which(trans$regi == regi2), ]$conn
if(sum(as.numeric(conns1))!= 0) {
for (conns_tmp in conns1) {
flow_regi1 <- 0
netflow_regi1 <- 0
for (tau2 in tau) {
#aggregate positive flows
flow_tmp1 <- v_transflow1[, , paste0(tau2, ".", conns_tmp)]*as.numeric(p_taulength[, , tau2]) #in GWh for value
flow_regi1 <- flow_regi1 + setNames(flow_tmp1/1000, NULL) #cumulate per border link... in TWh for volume
partMagPie1 <- partMagPie1 + setNames(flow_tmp1/1000, NULL) #cumulate per country... in TWh for volume
#estimating value of exports (the price paid is the one of country to which is exported [if exports is because marginal costs are lower])
regi_tmp_iso2 <- trans[match(conns_tmp, trans$conn), ]$reg #country to which is exported (ISO2)
regi_tmp_iso3 <- mapping[match(regi_tmp_iso2, mapping$LIMES_ISO2), ]$LIMES_ISO3 #country to which is exported (ISO3)
price_conn1 <- m_elecprices_tmp[regi_tmp_iso3, , tau2] #price in country to which is exported (price paid for the exports)
getItems(flow_tmp1, dim = 1) <- regi_tmp_iso3
value_tmp1 <- setNames(flow_tmp1, NULL)*(1-as.numeric(p_losses[, , conns_tmp]))*setNames(price_conn1, NULL)
getItems(value_tmp1, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
value1 <- value1 + value_tmp1
#calculate the NET EXPORTS (positive flows)
v_netflow1[, , paste0(tau2, ".", conns_tmp)] <- v_transflow1[, , paste0(tau2, ".", conns_tmp)]-v_transflow2[, , paste0(tau2, ".", conns_tmp)]*as.numeric(1-p_losses[, , conns_tmp])
#aggregate positive NET flows
netflow_tmp1 <- v_netflow1[, , paste0(tau2, ".", conns_tmp)]*as.numeric(p_taulength[, , tau2]) #in GWh for value
netflow_regi1 <- netflow_regi1 + setNames(netflow_tmp1/1000, NULL) #cumulate per border link... in TWh for volume
}
cap1 <- cap1 + setNames(v_captrans[, , conns_tmp], NULL)
#exports to every country (positive flows)
flow_regi <- setNames(flow_regi1, NULL)
getItems(flow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Exports to ", mapping[match(trans[match(conns_tmp, trans$conn), ]$reg, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (TWh/yr)")
expo1 <- mbind(expo1, setNames(flow_regi, a))
#net exports to every country (positive flows)
netflow_regi <- setNames(netflow_regi1, NULL)
getItems(netflow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Net exports to ", mapping[match(trans[match(conns_tmp, trans$conn), ]$reg, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (TWh/yr)")
netexpo1 <- mbind(netexpo1, setNames(netflow_regi, a))
#cross-border transmission capacity (positive flows)
cap_regi_tmp <- v_captrans[, , conns_tmp]
getItems(cap_regi_tmp, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Transmission capacity with ", mapping[match(trans[match(conns_tmp, trans$conn), ]$reg, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (GW)")
cap_regi1 <- mbind(cap_regi1, setNames(cap_regi_tmp, a))
}
}
#initialize variables to aggregate negative flows
partMagPie2 <- 0
cap2 <- 0
value2 <- 0
expo2 <- NULL
netexpo2 <- NULL
cap_regi2 <- NULL
#aggreate negative flows
conns2 <- trans[which(trans$reg == regi2), ]$conn
if(sum(as.numeric(conns2)) != 0) {
for (conns_tmp in conns2) {
flow_regi2 <- 0
netflow_regi2 <- 0
for (tau2 in tau) {
#aggregate negative flows
flow_tmp2 <- v_transflow2[, , paste0(tau2, ".", conns_tmp)]*as.numeric(p_taulength[, , tau2]) #in GWh for value
flow_regi2 <- flow_regi2 + setNames(flow_tmp2/1000, NULL) #cumulate per border link... in TWh for volume
partMagPie2 <- partMagPie2 + setNames(flow_tmp2/1000, NULL) #cumulate per country...in TWh for volume
#estimating value of exports (the price paid is the one of country to which is exported [if exports is because marginal costs are lower])
regi_tmp_iso2 <- trans[match(conns_tmp, trans$conn), ]$regi #country to which is exported (ISO2)
regi_tmp_iso3 <- mapping[match(regi_tmp_iso2, mapping$LIMES_ISO2), ]$LIMES_ISO3 #country to which is exported (ISO3)
price_conn2 <- m_elecprices_tmp[regi_tmp_iso3, , tau2] #price in country to which is exported (price paid for the exports)
getItems(flow_tmp2, dim = 1) <- regi_tmp_iso3
#setNames(flow_tmp2, NULL)
#setNames(price_conn2, NULL)
value_tmp2 <- setNames(flow_tmp2, NULL)*(1-as.numeric(p_losses[, , conns_tmp]))*setNames(price_conn2, NULL)
getItems(value_tmp2, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
value2 <- value2 + value_tmp2
#calculate the NET EXPORTS (negative flows)
v_netflow2[, , paste0(tau2, ".", conns_tmp)] <- v_transflow2[, , paste0(tau2, ".", conns_tmp)]-v_transflow1[, , paste0(tau2, ".", conns_tmp)]*as.numeric(1-p_losses[, , conns_tmp])
#aggregate negative NET flows
netflow_tmp2 <- v_netflow2[, , paste0(tau2, ".", conns_tmp)]*as.numeric(p_taulength[, , tau2]) #in GWh for value
netflow_regi2 <- netflow_regi2 + setNames(netflow_tmp2/1000, NULL) #cumulate per border link... in TWh for volume
}
cap2 <- cap2 + setNames(v_captrans[, , conns_tmp], NULL)
#exports to every country (negative flows)
flow_regi <- setNames(flow_regi2, NULL)
getItems(flow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Exports to ", mapping[match(trans[match(conns_tmp, trans$conn), ]$regi, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (TWh/yr)")
expo2 <- mbind(expo2, setNames(flow_regi, a))
#net exports to every country (negative flows)
netflow_regi <- setNames(netflow_regi2, NULL)
getItems(netflow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Net exports to ", mapping[match(trans[match(conns_tmp, trans$conn), ]$regi, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (TWh/yr)")
netexpo2 <- mbind(netexpo2, setNames(netflow_regi, a))
#cross-border transmission capacity
cap_regi_tmp <- v_captrans[, , conns_tmp]
getItems(cap_regi_tmp, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Transmission capacity with ", mapping[match(trans[match(conns_tmp, trans$conn), ]$regi, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (GW)")
cap_regi2 <- mbind(cap_regi2, setNames(cap_regi_tmp, a))
}
}
#For cross-border dependent data it is necessary to create the rows for each country (so all the countries have the same dimensions)
regi_tmp1 <- mapping[match(trans[match(conns1, trans$conn), ]$reg, mapping$LIMES_ISO2), ]$LIMES_ISO3
regi_tmp2 <- mapping[match(trans[match(conns2, trans$conn), ]$regi, mapping$LIMES_ISO2), ]$LIMES_ISO3
regi_noexp <- setdiff(mapping$LIMES_ISO3, union(regi_tmp1, regi_tmp2))
expo3 <- NULL
netexpo3 <- NULL
cap_regi3 <- NULL
for (regi_noexp_tmp in regi_noexp) {
#exports to every country
flow_regi <- setNames(flow_tmp2, NULL)*0
getItems(flow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Exports to ", regi_noexp_tmp, "|Electricity (TWh/yr)")
expo3 <- mbind(expo3, setNames(flow_regi, a))
#net exports to every country
netflow_regi <- setNames(netflow_tmp2, NULL)*0
getItems(netflow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Net exports to ", regi_noexp_tmp, "|Electricity (TWh/yr)")
netexpo3 <- mbind(netexpo3, setNames(netflow_regi, a))
#transmission capacity to every country
cap_regi_tmp <- cap_regi_tmp*0
getItems(cap_regi_tmp, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Transmission capacity with ", regi_noexp_tmp, "|Electricity (GW)")
cap_regi3 <- mbind(cap_regi3, setNames(cap_regi_tmp, a))
}
#concatenate exports (positive, negative and unexistant flows)
expo <- mbind(expo1, expo2, expo3)
expo_regi <- mbind(expo_regi, expo)
#concatenate net exports (positive, negative and unexistant flows)
netexpo <- mbind(netexpo1, netexpo2, netexpo3)
netexpo_regi <- mbind(netexpo_regi, netexpo)
#concatenate cross-border capacities (positive, negative and unexistant flows)
cap_regi4 <- mbind(cap_regi1, cap_regi2, cap_regi3)
cap_regi <- mbind(cap_regi, cap_regi4)
#sum positive and negative flows
partMagPie<-partMagPie1+partMagPie2
cap <- cap1 + cap2
value <- value1 + value2
#add country to the names
getNames(partMagPie)<-regi2
getNames(cap)<-regi2
#concatenate data from different countries (regi)
exports <- mbind(exports, partMagPie)
capexports <- mbind(capexports, cap)
valueexports <- mbind(valueexports, value)
}
# create MagPie object of exports volume and transmission capacity with iso3 regions
exports<-limesMapping(exports)
capexports<-limesMapping(capexports)
#MagPie object of value of exports was already created
#----------------------------------------------------------------------------------
#IMPORTS
imports <- NULL
capimports <- NULL
valueimports <- NULL
impo_regi <- NULL
capimports_km <- NULL
#estimate aggregated (total) imports from each country
for (regi2 in regi) {
#initialize variables to aggregate positive flows
partMagPie1 <- 0
cap1 <- 0
value1 <- 0
impo1 <- NULL
cap1_km <- 0
#aggregate the positive flows
conns1 <- trans[which(trans$reg == regi2), ]$conn
if(length(conns1) != 0) {
for (conns_tmp in conns1) {
flow_regi1 <- 0
for (tau2 in tau) {
#aggregate positive flows
flow_tmp1 <- v_transflow1[, , paste0(tau2, ".", conns_tmp)]*as.numeric(p_taulength[, , tau2])*(1-as.numeric(p_losses[, , conns_tmp])) #in GWh for value
flow_regi1 <- flow_regi1 + setNames(flow_tmp1/1000, NULL) #cumulate per border link... in TWh for volume
partMagPie1 <- partMagPie1 + setNames(flow_tmp1/1000, NULL) #cumulate per country... in TWh for volume
#estimating value of imports (the price paid is the one of the importer country [if imports is because marginal costs are higher])
regi_tmp_iso2 <- trans[match(conns_tmp, trans$conn), ]$regi #country from which is imported (ISO2)
regi_tmp_iso3 <- mapping[match(regi_tmp_iso2, mapping$LIMES_ISO2), ]$LIMES_ISO3 #country from which is imported (ISO3)
price_conn1 <- m_elecprices_tmp[mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3, , tau2] #price in country that imports (price paid for the exports)
getItems(flow_tmp1, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
value_tmp1 <- setNames(flow_tmp1, NULL)*setNames(price_conn1, NULL)
getItems(value_tmp1, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
value1 <- value1 + value_tmp1
}
cap1 <- cap1 + setNames(v_captrans[, , conns_tmp], NULL)
cap1_km <- cap1_km + setNames(v_captrans[, , conns_tmp]*p_length[, , conns_tmp], NULL)
#imports from every country (positive flows)
flow_regi <- setNames(flow_regi1, NULL)
getItems(flow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Imports from ", mapping[match(trans[match(conns_tmp, trans$conn), ]$regi, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (TWh/yr)")
impo1 <- mbind(impo1, setNames(flow_regi, a))
}
}
#initialize variables to aggregate negative flows
partMagPie2 <- 0
cap2 <- 0
value2 <- 0
impo2 <- NULL
cap2_km <- 0
#aggreate negative flows
conns2 <- trans[which(trans$regi == regi2), ]$conn
if(sum(as.numeric(conns2)) != 0) {
for (conns_tmp in conns2) {
flow_regi2 <- 0
for (tau2 in tau) {
#aggregate negative flows
flow_tmp2 <- v_transflow2[, , paste0(tau2, ".", conns_tmp)]*as.numeric(p_taulength[, , tau2])*(1-as.numeric(p_losses[, , conns_tmp])) #in GWh for value
flow_regi2 <- flow_regi2 + setNames(flow_tmp2/1000, NULL) #cumulate per border link... in TWh for volume
partMagPie2 <- partMagPie2 + setNames(flow_tmp2/1000, NULL) #cumulate per country.. in TWh for volume
#estimating value of imports (the price paid is the one of the importer country [if imports is because marginal costs are higher])
regi_tmp_iso2 <- trans[match(conns_tmp, trans$conn), ]$reg #country from which is imported (ISO2)
regi_tmp_iso3 <- mapping[match(regi_tmp_iso2, mapping$LIMES_ISO2), ]$LIMES_ISO3 #country from which is imported (ISO3)
price_conn2 <- m_elecprices_tmp[mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3, , tau2] #price in country that imports (price paid for the exports)
getItems(flow_tmp2, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
value_tmp2 <- setNames(flow_tmp2, NULL)*setNames(price_conn2, NULL)
getItems(value_tmp2, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
value2 <- value2 + value_tmp2
}
cap2 <- cap2 + setNames(v_captrans[, , conns_tmp], NULL)
cap2_km <- cap2_km + setNames(v_captrans[, , conns_tmp]*p_length[, , conns_tmp], NULL)
#imports from every country (negative flows)
flow_regi <- setNames(flow_regi2, NULL)
getItems(flow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Imports from ", as.vector(mapping[match(trans[match(conns_tmp, trans$conn), ]$reg, mapping$LIMES_ISO2), ]$LIMES_ISO3), "|Electricity (TWh/yr)")
impo2 <- mbind(impo2, setNames(flow_regi, a))
}
}
#it is necessary to create the rows for each country (so all the countries have the same dimensions)
regi_tmp1 <- mapping[match(trans[match(conns1, trans$conn), ]$regi, mapping$LIMES_ISO2), ]$LIMES_ISO3
regi_tmp2 <- mapping[match(trans[match(conns2, trans$conn), ]$reg, mapping$LIMES_ISO2), ]$LIMES_ISO3
regi_noimp <- setdiff(mapping$LIMES_ISO3, union(regi_tmp1, regi_tmp2))
impo3 <- NULL
for (regi_noimp_tmp in regi_noimp) {
#exports to every country (negative flows)
flow_regi <- setNames(flow_tmp2/1000, NULL)*0
getItems(flow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Imports from ", regi_noimp_tmp, "|Electricity (TWh/yr)")
impo3 <- mbind(impo3, setNames(flow_regi, a))
}
#concatenate imports (positive, negative and unexistant flows)
impo <- mbind(impo1, impo2, impo3)
impo_regi <- mbind(impo_regi, impo)
#sum positive and negative flows
partMagPie<-partMagPie1+partMagPie2
cap <- cap1 + cap2
cap_km <- cap1_km + cap2_km
value <- value1 + value2
#add country to the names
getNames(partMagPie)<-regi2
getNames(cap)<-regi2
getNames(cap_km)<-regi2
#concatenate data from different countries (regi)
imports <- mbind(imports, partMagPie)
capimports <- mbind(capimports, cap)
capimports_km <- mbind(capimports_km, cap_km)
valueimports <- mbind(valueimports, value)
}
# create MagPie object of imports volume and transmission capacity with iso3 regions
imports <- limesMapping(imports)
capimports <- limesMapping(capimports)
capimports_km <- limesMapping(capimports_km)
#MagPie object of value of imports was already created
#--------------------------------------------------------------------------------------------------
#REPORTING THE EXCHANGE (EXPORTS, IMPORTS AND NET EXPORTS)
#add variable name for the report
tmp1<-setNames(exports, "Secondary Energy|Electricity|Exports (TWh/yr)")
tmp2 <- setNames(imports, "Secondary Energy|Electricity|Imports (TWh/yr)")
# add exports and imports
tmp3 <- mbind(tmp1, tmp2)
#----------------------------------------------------------------------------------
#NET EXPORTS/IMPORTS
tmp4 <- NULL
#Net imports to/from Russia
v_netimports_ru <- readGDX(gdx, name = "v_netimports_ru", field = "l", format = "first_found")
v_netimports_ru <- limesMapping(v_netimports_ru)
tmp4 <- mbind(tmp4, setNames(dimSums(v_netimports_ru * p_taulength, dim = 3) / 1000, "Net Imports from RUS|Electricity (TWh/yr)"))
tmp4 <- mbind(tmp4, setNames(dimSums(-v_netimports_ru * p_taulength, dim = 3) / 1000, "Net Exports to RUS|Electricity (TWh/yr)"))
#Aggregate
tmp4 <- mbind(tmp4, setNames(exports - imports - dimSums(v_netimports_ru * p_taulength, dim = 3) / 1000, "Secondary Energy|Electricity|Net Exports (TWh/yr)"))
tmp4 <- mbind(tmp4, setNames(imports - exports + dimSums(v_netimports_ru * p_taulength, dim = 3) / 1000, "Secondary Energy|Electricity|Net Imports (TWh/yr)"))
# add exchange values
tmp5 <- mbind(tmp3, tmp4)
#----------------------------------------------------------------------------------
#REPORTING THE EXPORT AND IMPORT TRANSMISSION CAPACITY
#add variable name transmission capacity
tmp6<-setNames(capexports[, as.numeric(tt), ], "Export Transmission Capacity|Electricity (GW)")
tmp7<-setNames(capimports[, as.numeric(tt), ], "Import Transmission Capacity|Electricity (GW)")
#add capacity to export and import
tmp8 <- mbind(tmp6, tmp7)
#concatenate exchange and capacities
tmp9 <- mbind(tmp5, tmp8)
#transmission capacity (under current configuration, export and import capacity are the same)
tmp10 <- NULL
tmp10 <- setNames(tmp7, "Capacity|Electricity|Transmission Grid (GW)")
tmp10 <- mbind(tmp10, setNames(capimports_km[, as.numeric(tt), ], "Capacity|Electricity|Transmission Grid-km (GWkm)"))
#concatenate
tmp11 <- mbind(tmp9, tmp10)
#REPORTING THE VALUE OF IMPORTS AND EXPORTS
tmp12 <- NULL
tmp12 <- setNames(valueexports, "Revenue|Electricity|Exports (billion eur2010/yr)")
tmp12 <- mbind(tmp12, setNames(valueimports, "Cost|Electricity|Imports (billion eur2010/yr)"))
tmp12 <- mbind(tmp12, setNames(valueimports-valueexports, "Total Energy System Cost|Power Sector|Trade Costs (billion eur2010/yr)"))
#concatenate
tmp13 <- mbind(tmp11, tmp12)
#REPORTING THE EXPORTS; IMPORTS AND NET EXPORTS FOR EACH CROSS-BORDER LINK
tmp14 <- NULL
tmp14 <- mbind(expo_regi, impo_regi, netexpo_regi)
tmp14 <- mbind(tmp14, cap_regi[, as.numeric(tt), ])
# erasing all the data regarding connections that do not exist (created before to fit the size of the variables)
for (regi2 in getItems(tmp14, dim = 1)) { for (name in getNames(tmp14)){
if (sum(tmp14[regi2, , name]) == 0) {
tmp14[regi2, , name] <- NA
}
}}
#concatenate all
tmp <- mbind(tmp13, tmp14)
return(tmp)
}
pik-piam/limes documentation built on Jan. 27, 2024, 4:45 a.m.
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Defines functions reportExchange
Documented in reportExchange
#' Read in GDX and calculate electricity exchange, value of exchange and aggregated transmission capacites, used in convGDX2MIF.R for the reporting
#'
#' Read in electricity exchange data 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
#' @return MAgPIE object - contains the capacity variables
#' @author Sebastian Osorio, Renato Rodrigues
#' @seealso \code{\link{convGDX2MIF}}
#' @examples
#'
#' \dontrun{reportExchange(gdx)}
#'
#' @importFrom gdx readGDX
#' @importFrom magclass mbind setNames dimSums getSets getSets<- as.magpie getNames<- getItems<- getItems
#' @export
#'
reportExchange <- function(gdx) {
# read parameters and sets
trans <- readGDX(gdx, name = "trans") #set of cross-border transmission lines (numeric)
tau <- readGDX(gdx, name = "tau") #set of tau
regi <- readGDX(gdx, name = "regi") #set of countries
tt <- readGDX(gdx, name = "t") #set of time
tt <- readGDX(gdx, name = "t", field = "l", format = "first_found") # time set
t0 <- tt[1]
c_esmdisrate <- readGDX(gdx, name = "c_esmdisrate", field = "l", format = "first_found") #interest rate
p_tedataconn <- readGDX(gdx, name = "p_tedataconn", field = "l", format = "first_found") #technical parameters of transmission
p_ts <- readGDX(gdx, name = "p_ts", field = "l", format = "first_found") #time step
p_taulength <- readGDX(gdx, name = c("p_taulength", "pm_taulength"), field = "l", format = "first_found")[, , tau] #number of hours/year per tau
# read variables
v_transflow1 <- readGDX(gdx, name = "v_transflow1", field = "l", format = "first_found")
v_transflow2 <- readGDX(gdx, name = "v_transflow2", field = "l", format = "first_found")
v_captrans <- readGDX(gdx, name = "v_captrans", field = "l", format = "first_found")
#define the losses
p_losses <- p_tedataconn[, , "loss"]
p_length <- p_tedataconn[, , "length"]
#ELECTRICITY PRICES (needed for computing import and export prices)
# read variables
m_elecprices <- readGDX(gdx, name = "q_sebal", field = "m", format = "first_found")
m_elecprices <- m_elecprices[, , "seel"]
# create MagPie object of m_elecprices with iso3 regions
m_elecprices <- limesMapping(m_elecprices)[, , tau]
# calculate marginal value per tau
m_elecprices = m_elecprices/p_taulength
#compute factor to discount average marginal values
f_npv <- as.numeric(p_ts)*exp(-as.numeric(c_esmdisrate)*(as.numeric(tt)-as.numeric(t0)))
#discounting marginal values [Geur/GWh]
m_elecprices_tmp <- NULL
for (t2 in 1:length(tt)) {
m_elecprices_tmp <- mbind(m_elecprices_tmp, m_elecprices[, t2, ]/f_npv[t2])
}
# settings mapping path
mappingPath <- system.file("extdata", "LIMES_country_ISO_3.csv", package = "limes")
# reading mapping file
mapping <- read.csv(mappingPath, sep = ";")
#Create variables for NET EXPORTS of the same size and forman than v_transflow
v_netflow1 <- v_transflow1*0
v_netflow2 <- v_transflow2*0
#----------------------------------------------------------------------------------
#EXPORTS
exports <- NULL
capexports <- NULL
valueexports <- NULL
expo_regi <- NULL
netexpo_regi <- NULL
cap_regi <- NULL
#estimate aggregated (total) exports from each country
for (regi2 in regi) {
#initialize variables to aggregate positive flows
partMagPie1<-0
cap1<-0
value1 <- 0
expo1 <- NULL
netexpo1 <- NULL
cap_regi1 <- NULL
#aggregate the positive flows
conns1 <- trans[which(trans$regi == regi2), ]$conn
if(sum(as.numeric(conns1))!= 0) {
for (conns_tmp in conns1) {
flow_regi1 <- 0
netflow_regi1 <- 0
for (tau2 in tau) {
#aggregate positive flows
flow_tmp1 <- v_transflow1[, , paste0(tau2, ".", conns_tmp)]*as.numeric(p_taulength[, , tau2]) #in GWh for value
flow_regi1 <- flow_regi1 + setNames(flow_tmp1/1000, NULL) #cumulate per border link... in TWh for volume
partMagPie1 <- partMagPie1 + setNames(flow_tmp1/1000, NULL) #cumulate per country... in TWh for volume
#estimating value of exports (the price paid is the one of country to which is exported [if exports is because marginal costs are lower])
regi_tmp_iso2 <- trans[match(conns_tmp, trans$conn), ]$reg #country to which is exported (ISO2)
regi_tmp_iso3 <- mapping[match(regi_tmp_iso2, mapping$LIMES_ISO2), ]$LIMES_ISO3 #country to which is exported (ISO3)
price_conn1 <- m_elecprices_tmp[regi_tmp_iso3, , tau2] #price in country to which is exported (price paid for the exports)
getItems(flow_tmp1, dim = 1) <- regi_tmp_iso3
value_tmp1 <- setNames(flow_tmp1, NULL)*(1-as.numeric(p_losses[, , conns_tmp]))*setNames(price_conn1, NULL)
getItems(value_tmp1, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
value1 <- value1 + value_tmp1
#calculate the NET EXPORTS (positive flows)
v_netflow1[, , paste0(tau2, ".", conns_tmp)] <- v_transflow1[, , paste0(tau2, ".", conns_tmp)]-v_transflow2[, , paste0(tau2, ".", conns_tmp)]*as.numeric(1-p_losses[, , conns_tmp])
#aggregate positive NET flows
netflow_tmp1 <- v_netflow1[, , paste0(tau2, ".", conns_tmp)]*as.numeric(p_taulength[, , tau2]) #in GWh for value
netflow_regi1 <- netflow_regi1 + setNames(netflow_tmp1/1000, NULL) #cumulate per border link... in TWh for volume
}
cap1 <- cap1 + setNames(v_captrans[, , conns_tmp], NULL)
#exports to every country (positive flows)
flow_regi <- setNames(flow_regi1, NULL)
getItems(flow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Exports to ", mapping[match(trans[match(conns_tmp, trans$conn), ]$reg, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (TWh/yr)")
expo1 <- mbind(expo1, setNames(flow_regi, a))
#net exports to every country (positive flows)
netflow_regi <- setNames(netflow_regi1, NULL)
getItems(netflow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Net exports to ", mapping[match(trans[match(conns_tmp, trans$conn), ]$reg, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (TWh/yr)")
netexpo1 <- mbind(netexpo1, setNames(netflow_regi, a))
#cross-border transmission capacity (positive flows)
cap_regi_tmp <- v_captrans[, , conns_tmp]
getItems(cap_regi_tmp, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Transmission capacity with ", mapping[match(trans[match(conns_tmp, trans$conn), ]$reg, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (GW)")
cap_regi1 <- mbind(cap_regi1, setNames(cap_regi_tmp, a))
}
}
#initialize variables to aggregate negative flows
partMagPie2 <- 0
cap2 <- 0
value2 <- 0
expo2 <- NULL
netexpo2 <- NULL
cap_regi2 <- NULL
#aggreate negative flows
conns2 <- trans[which(trans$reg == regi2), ]$conn
if(sum(as.numeric(conns2)) != 0) {
for (conns_tmp in conns2) {
flow_regi2 <- 0
netflow_regi2 <- 0
for (tau2 in tau) {
#aggregate negative flows
flow_tmp2 <- v_transflow2[, , paste0(tau2, ".", conns_tmp)]*as.numeric(p_taulength[, , tau2]) #in GWh for value
flow_regi2 <- flow_regi2 + setNames(flow_tmp2/1000, NULL) #cumulate per border link... in TWh for volume
partMagPie2 <- partMagPie2 + setNames(flow_tmp2/1000, NULL) #cumulate per country...in TWh for volume
#estimating value of exports (the price paid is the one of country to which is exported [if exports is because marginal costs are lower])
regi_tmp_iso2 <- trans[match(conns_tmp, trans$conn), ]$regi #country to which is exported (ISO2)
regi_tmp_iso3 <- mapping[match(regi_tmp_iso2, mapping$LIMES_ISO2), ]$LIMES_ISO3 #country to which is exported (ISO3)
price_conn2 <- m_elecprices_tmp[regi_tmp_iso3, , tau2] #price in country to which is exported (price paid for the exports)
getItems(flow_tmp2, dim = 1) <- regi_tmp_iso3
#setNames(flow_tmp2, NULL)
#setNames(price_conn2, NULL)
value_tmp2 <- setNames(flow_tmp2, NULL)*(1-as.numeric(p_losses[, , conns_tmp]))*setNames(price_conn2, NULL)
getItems(value_tmp2, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
value2 <- value2 + value_tmp2
#calculate the NET EXPORTS (negative flows)
v_netflow2[, , paste0(tau2, ".", conns_tmp)] <- v_transflow2[, , paste0(tau2, ".", conns_tmp)]-v_transflow1[, , paste0(tau2, ".", conns_tmp)]*as.numeric(1-p_losses[, , conns_tmp])
#aggregate negative NET flows
netflow_tmp2 <- v_netflow2[, , paste0(tau2, ".", conns_tmp)]*as.numeric(p_taulength[, , tau2]) #in GWh for value
netflow_regi2 <- netflow_regi2 + setNames(netflow_tmp2/1000, NULL) #cumulate per border link... in TWh for volume
}
cap2 <- cap2 + setNames(v_captrans[, , conns_tmp], NULL)
#exports to every country (negative flows)
flow_regi <- setNames(flow_regi2, NULL)
getItems(flow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Exports to ", mapping[match(trans[match(conns_tmp, trans$conn), ]$regi, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (TWh/yr)")
expo2 <- mbind(expo2, setNames(flow_regi, a))
#net exports to every country (negative flows)
netflow_regi <- setNames(netflow_regi2, NULL)
getItems(netflow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Net exports to ", mapping[match(trans[match(conns_tmp, trans$conn), ]$regi, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (TWh/yr)")
netexpo2 <- mbind(netexpo2, setNames(netflow_regi, a))
#cross-border transmission capacity
cap_regi_tmp <- v_captrans[, , conns_tmp]
getItems(cap_regi_tmp, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Transmission capacity with ", mapping[match(trans[match(conns_tmp, trans$conn), ]$regi, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (GW)")
cap_regi2 <- mbind(cap_regi2, setNames(cap_regi_tmp, a))
}
}
#For cross-border dependent data it is necessary to create the rows for each country (so all the countries have the same dimensions)
regi_tmp1 <- mapping[match(trans[match(conns1, trans$conn), ]$reg, mapping$LIMES_ISO2), ]$LIMES_ISO3
regi_tmp2 <- mapping[match(trans[match(conns2, trans$conn), ]$regi, mapping$LIMES_ISO2), ]$LIMES_ISO3
regi_noexp <- setdiff(mapping$LIMES_ISO3, union(regi_tmp1, regi_tmp2))
expo3 <- NULL
netexpo3 <- NULL
cap_regi3 <- NULL
for (regi_noexp_tmp in regi_noexp) {
#exports to every country
flow_regi <- setNames(flow_tmp2, NULL)*0
getItems(flow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Exports to ", regi_noexp_tmp, "|Electricity (TWh/yr)")
expo3 <- mbind(expo3, setNames(flow_regi, a))
#net exports to every country
netflow_regi <- setNames(netflow_tmp2, NULL)*0
getItems(netflow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Net exports to ", regi_noexp_tmp, "|Electricity (TWh/yr)")
netexpo3 <- mbind(netexpo3, setNames(netflow_regi, a))
#transmission capacity to every country
cap_regi_tmp <- cap_regi_tmp*0
getItems(cap_regi_tmp, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Transmission capacity with ", regi_noexp_tmp, "|Electricity (GW)")
cap_regi3 <- mbind(cap_regi3, setNames(cap_regi_tmp, a))
}
#concatenate exports (positive, negative and unexistant flows)
expo <- mbind(expo1, expo2, expo3)
expo_regi <- mbind(expo_regi, expo)
#concatenate net exports (positive, negative and unexistant flows)
netexpo <- mbind(netexpo1, netexpo2, netexpo3)
netexpo_regi <- mbind(netexpo_regi, netexpo)
#concatenate cross-border capacities (positive, negative and unexistant flows)
cap_regi4 <- mbind(cap_regi1, cap_regi2, cap_regi3)
cap_regi <- mbind(cap_regi, cap_regi4)
#sum positive and negative flows
partMagPie<-partMagPie1+partMagPie2
cap <- cap1 + cap2
value <- value1 + value2
#add country to the names
getNames(partMagPie)<-regi2
getNames(cap)<-regi2
#concatenate data from different countries (regi)
exports <- mbind(exports, partMagPie)
capexports <- mbind(capexports, cap)
valueexports <- mbind(valueexports, value)
}
# create MagPie object of exports volume and transmission capacity with iso3 regions
exports<-limesMapping(exports)
capexports<-limesMapping(capexports)
#MagPie object of value of exports was already created
#----------------------------------------------------------------------------------
#IMPORTS
imports <- NULL
capimports <- NULL
valueimports <- NULL
impo_regi <- NULL
capimports_km <- NULL
#estimate aggregated (total) imports from each country
for (regi2 in regi) {
#initialize variables to aggregate positive flows
partMagPie1 <- 0
cap1 <- 0
value1 <- 0
impo1 <- NULL
cap1_km <- 0
#aggregate the positive flows
conns1 <- trans[which(trans$reg == regi2), ]$conn
if(length(conns1) != 0) {
for (conns_tmp in conns1) {
flow_regi1 <- 0
for (tau2 in tau) {
#aggregate positive flows
flow_tmp1 <- v_transflow1[, , paste0(tau2, ".", conns_tmp)]*as.numeric(p_taulength[, , tau2])*(1-as.numeric(p_losses[, , conns_tmp])) #in GWh for value
flow_regi1 <- flow_regi1 + setNames(flow_tmp1/1000, NULL) #cumulate per border link... in TWh for volume
partMagPie1 <- partMagPie1 + setNames(flow_tmp1/1000, NULL) #cumulate per country... in TWh for volume
#estimating value of imports (the price paid is the one of the importer country [if imports is because marginal costs are higher])
regi_tmp_iso2 <- trans[match(conns_tmp, trans$conn), ]$regi #country from which is imported (ISO2)
regi_tmp_iso3 <- mapping[match(regi_tmp_iso2, mapping$LIMES_ISO2), ]$LIMES_ISO3 #country from which is imported (ISO3)
price_conn1 <- m_elecprices_tmp[mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3, , tau2] #price in country that imports (price paid for the exports)
getItems(flow_tmp1, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
value_tmp1 <- setNames(flow_tmp1, NULL)*setNames(price_conn1, NULL)
getItems(value_tmp1, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
value1 <- value1 + value_tmp1
}
cap1 <- cap1 + setNames(v_captrans[, , conns_tmp], NULL)
cap1_km <- cap1_km + setNames(v_captrans[, , conns_tmp]*p_length[, , conns_tmp], NULL)
#imports from every country (positive flows)
flow_regi <- setNames(flow_regi1, NULL)
getItems(flow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Imports from ", mapping[match(trans[match(conns_tmp, trans$conn), ]$regi, mapping$LIMES_ISO2), ]$LIMES_ISO3, "|Electricity (TWh/yr)")
impo1 <- mbind(impo1, setNames(flow_regi, a))
}
}
#initialize variables to aggregate negative flows
partMagPie2 <- 0
cap2 <- 0
value2 <- 0
impo2 <- NULL
cap2_km <- 0
#aggreate negative flows
conns2 <- trans[which(trans$regi == regi2), ]$conn
if(sum(as.numeric(conns2)) != 0) {
for (conns_tmp in conns2) {
flow_regi2 <- 0
for (tau2 in tau) {
#aggregate negative flows
flow_tmp2 <- v_transflow2[, , paste0(tau2, ".", conns_tmp)]*as.numeric(p_taulength[, , tau2])*(1-as.numeric(p_losses[, , conns_tmp])) #in GWh for value
flow_regi2 <- flow_regi2 + setNames(flow_tmp2/1000, NULL) #cumulate per border link... in TWh for volume
partMagPie2 <- partMagPie2 + setNames(flow_tmp2/1000, NULL) #cumulate per country.. in TWh for volume
#estimating value of imports (the price paid is the one of the importer country [if imports is because marginal costs are higher])
regi_tmp_iso2 <- trans[match(conns_tmp, trans$conn), ]$reg #country from which is imported (ISO2)
regi_tmp_iso3 <- mapping[match(regi_tmp_iso2, mapping$LIMES_ISO2), ]$LIMES_ISO3 #country from which is imported (ISO3)
price_conn2 <- m_elecprices_tmp[mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3, , tau2] #price in country that imports (price paid for the exports)
getItems(flow_tmp2, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
value_tmp2 <- setNames(flow_tmp2, NULL)*setNames(price_conn2, NULL)
getItems(value_tmp2, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
value2 <- value2 + value_tmp2
}
cap2 <- cap2 + setNames(v_captrans[, , conns_tmp], NULL)
cap2_km <- cap2_km + setNames(v_captrans[, , conns_tmp]*p_length[, , conns_tmp], NULL)
#imports from every country (negative flows)
flow_regi <- setNames(flow_regi2, NULL)
getItems(flow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Imports from ", as.vector(mapping[match(trans[match(conns_tmp, trans$conn), ]$reg, mapping$LIMES_ISO2), ]$LIMES_ISO3), "|Electricity (TWh/yr)")
impo2 <- mbind(impo2, setNames(flow_regi, a))
}
}
#it is necessary to create the rows for each country (so all the countries have the same dimensions)
regi_tmp1 <- mapping[match(trans[match(conns1, trans$conn), ]$regi, mapping$LIMES_ISO2), ]$LIMES_ISO3
regi_tmp2 <- mapping[match(trans[match(conns2, trans$conn), ]$reg, mapping$LIMES_ISO2), ]$LIMES_ISO3
regi_noimp <- setdiff(mapping$LIMES_ISO3, union(regi_tmp1, regi_tmp2))
impo3 <- NULL
for (regi_noimp_tmp in regi_noimp) {
#exports to every country (negative flows)
flow_regi <- setNames(flow_tmp2/1000, NULL)*0
getItems(flow_regi, dim = 1) <- mapping[match(regi2, mapping$LIMES_ISO2), ]$LIMES_ISO3
a <- paste0("Imports from ", regi_noimp_tmp, "|Electricity (TWh/yr)")
impo3 <- mbind(impo3, setNames(flow_regi, a))
}
#concatenate imports (positive, negative and unexistant flows)
impo <- mbind(impo1, impo2, impo3)
impo_regi <- mbind(impo_regi, impo)
#sum positive and negative flows
partMagPie<-partMagPie1+partMagPie2
cap <- cap1 + cap2
cap_km <- cap1_km + cap2_km
value <- value1 + value2
#add country to the names
getNames(partMagPie)<-regi2
getNames(cap)<-regi2
getNames(cap_km)<-regi2
#concatenate data from different countries (regi)
imports <- mbind(imports, partMagPie)
capimports <- mbind(capimports, cap)
capimports_km <- mbind(capimports_km, cap_km)
valueimports <- mbind(valueimports, value)
}
# create MagPie object of imports volume and transmission capacity with iso3 regions
imports <- limesMapping(imports)
capimports <- limesMapping(capimports)
capimports_km <- limesMapping(capimports_km)
#MagPie object of value of imports was already created
#--------------------------------------------------------------------------------------------------
#REPORTING THE EXCHANGE (EXPORTS, IMPORTS AND NET EXPORTS)
#add variable name for the report
tmp1<-setNames(exports, "Secondary Energy|Electricity|Exports (TWh/yr)")
tmp2 <- setNames(imports, "Secondary Energy|Electricity|Imports (TWh/yr)")
# add exports and imports
tmp3 <- mbind(tmp1, tmp2)
#----------------------------------------------------------------------------------
#NET EXPORTS/IMPORTS
tmp4 <- NULL
#Net imports to/from Russia
v_netimports_ru <- readGDX(gdx, name = "v_netimports_ru", field = "l", format = "first_found")
v_netimports_ru <- limesMapping(v_netimports_ru)
tmp4 <- mbind(tmp4, setNames(dimSums(v_netimports_ru * p_taulength, dim = 3) / 1000, "Net Imports from RUS|Electricity (TWh/yr)"))
tmp4 <- mbind(tmp4, setNames(dimSums(-v_netimports_ru * p_taulength, dim = 3) / 1000, "Net Exports to RUS|Electricity (TWh/yr)"))
#Aggregate
tmp4 <- mbind(tmp4, setNames(exports - imports - dimSums(v_netimports_ru * p_taulength, dim = 3) / 1000, "Secondary Energy|Electricity|Net Exports (TWh/yr)"))
tmp4 <- mbind(tmp4, setNames(imports - exports + dimSums(v_netimports_ru * p_taulength, dim = 3) / 1000, "Secondary Energy|Electricity|Net Imports (TWh/yr)"))
# add exchange values
tmp5 <- mbind(tmp3, tmp4)
#----------------------------------------------------------------------------------
#REPORTING THE EXPORT AND IMPORT TRANSMISSION CAPACITY
#add variable name transmission capacity
tmp6<-setNames(capexports[, as.numeric(tt), ], "Export Transmission Capacity|Electricity (GW)")
tmp7<-setNames(capimports[, as.numeric(tt), ], "Import Transmission Capacity|Electricity (GW)")
#add capacity to export and import
tmp8 <- mbind(tmp6, tmp7)
#concatenate exchange and capacities
tmp9 <- mbind(tmp5, tmp8)
#transmission capacity (under current configuration, export and import capacity are the same)
tmp10 <- NULL
tmp10 <- setNames(tmp7, "Capacity|Electricity|Transmission Grid (GW)")
tmp10 <- mbind(tmp10, setNames(capimports_km[, as.numeric(tt), ], "Capacity|Electricity|Transmission Grid-km (GWkm)"))
#concatenate
tmp11 <- mbind(tmp9, tmp10)
#REPORTING THE VALUE OF IMPORTS AND EXPORTS
tmp12 <- NULL
tmp12 <- setNames(valueexports, "Revenue|Electricity|Exports (billion eur2010/yr)")
tmp12 <- mbind(tmp12, setNames(valueimports, "Cost|Electricity|Imports (billion eur2010/yr)"))
tmp12 <- mbind(tmp12, setNames(valueimports-valueexports, "Total Energy System Cost|Power Sector|Trade Costs (billion eur2010/yr)"))
#concatenate
tmp13 <- mbind(tmp11, tmp12)
#REPORTING THE EXPORTS; IMPORTS AND NET EXPORTS FOR EACH CROSS-BORDER LINK
tmp14 <- NULL
tmp14 <- mbind(expo_regi, impo_regi, netexpo_regi)
tmp14 <- mbind(tmp14, cap_regi[, as.numeric(tt), ])
# erasing all the data regarding connections that do not exist (created before to fit the size of the variables)
for (regi2 in getItems(tmp14, dim = 1)) { for (name in getNames(tmp14)){
if (sum(tmp14[regi2, , name]) == 0) {
tmp14[regi2, , name] <- NA
}
}}
#concatenate all
tmp <- mbind(tmp13, tmp14)
return(tmp)
}
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