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Commit f4bc4159 authored by Marianna Rottoli's avatar Marianna Rottoli
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Added plots for FE road transp and per capita.

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scripts/output/comparison/EDGEcomparison.R
+ 10
− 10
View file @ f4bc4159
......@@ -35,7 +35,7 @@ gdx_name = "fulldata.gdx"
emi_all = NULL
salescomp_all = NULL
fleet_all = NULL
EJLDV_all = NULL
EJroad_all = NULL
EJmode_all = NULL
ESmodecap_all = NULL
CO2km_int_newsales_all = NULL
......@@ -112,15 +112,15 @@ fleetFun = function(vintcomp, newcomp, sharesVS1){
}
EJLDVFun <- function(demandEJ){
demandEJ = demandEJ[subsector_L1 == "trn_pass_road_LDV_4W",]
EJroadFun <- function(demandEJ){
demandEJ = demandEJ[subsector_L3 %in% c("trn_pass_road", "trn_freight_road"),]
demandEJ <- demandEJ[, c("sector", "subsector_L3", "subsector_L2", "subsector_L1", "vehicle_type", "technology", "iso", "year", "demand_EJ")]
demandEJ = merge(demandEJ, REMIND2ISO_MAPPING, by = "iso")
demandEJ[technology == "Hybrid Liquids", technology := "Liquids"]
demandEJ[technology == "FCEV", technology := "Hydrogen"]
demandEJ[technology == "BEV", technology := "Electricity"]
demandEJ = demandEJ[, .(demand_EJ = sum(demand_EJ)), by = c("region", "year", "technology")]
demandEJ[technology %in% c("BEV", "Electric"), technology := "Electricity"]
demandEJ[subsector_L1 %in% c("trn_pass_road_bus_tmp_subsector_L1", "Bus_tmp_subsector_L1"), subsector_L1 := "Bus_tmp_subsector_L1"]
demandEJ = demandEJ[, .(demand_EJ = sum(demand_EJ)), by = c("region", "year", "technology", "subsector_L1")]
return(demandEJ)
}
......@@ -351,7 +351,7 @@ for (outputdir in outputdirs) {
## calculate fleet compositons
fleet = fleetFun(vintcomp, newcomp, sharesVS1)
## calculate EJ from LDVs by technology
EJLDV = EJLDVFun(demandEJ)
EJroad = EJroadFun(demandEJ)
## calculate FE demand by mode
EJmode = EJmodeFun(demandEJ)
## calculate ES demand per capita
......@@ -366,7 +366,7 @@ for (outputdir in outputdirs) {
## add scenario dimension to the results
fleet[, scenario := as.character(unique(miffile$scenario))]
salescomp[, scenario := unique(miffile$scenario)]
EJLDV[, scenario := as.character(unique(miffile$scenario))]
EJroad[, scenario := as.character(unique(miffile$scenario))]
EJmode[, scenario := as.character(unique(miffile$scenario))]
ESmodecap[, scenario := as.character(unique(miffile$scenario))]
CO2km_int_newsales[, scenario := as.character(unique(miffile$scenario))]
......@@ -376,7 +376,7 @@ for (outputdir in outputdirs) {
## rbind scenarios
salescomp_all = rbind(salescomp_all, salescomp)
fleet_all = rbind(fleet_all, fleet)
EJLDV_all = rbind(EJLDV_all, EJLDV)
EJroad_all = rbind(EJroad_all, EJroad)
EJmode_all = rbind(EJmode_all, EJmode)
ESmodecap_all = rbind(ESmodecap_all, ESmodecap)
CO2km_int_newsales_all = rbind(CO2km_int_newsales_all, CO2km_int_newsales)
......@@ -392,7 +392,7 @@ dash_template = "EDGEdashboard.Rmd"
saveRDS(EJmode_all, paste0(outdir, "/EJmode_all.RDS"))
saveRDS(salescomp_all, paste0(outdir, "/salescomp_all.RDS"))
saveRDS(fleet_all, paste0(outdir, "/fleet_all.RDS"))
saveRDS(EJLDV_all, paste0(outdir, "/EJLDV_all.RDS"))
saveRDS(EJroad_all, paste0(outdir, "/EJroad_all.RDS"))
saveRDS(ESmodecap_all, paste0(outdir, "/ESmodecap_all.RDS"))
saveRDS(CO2km_int_newsales_all, paste0(outdir, "/CO2km_int_newsales_all.RDS"))
saveRDS(EJfuels_all, paste0(outdir, "/EJfuels_all.RDS"))
......
scripts/output/comparison/notebook_templates/EDGETransportComparison.Rmd
+ 72
− 28
View file @ f4bc4159
......@@ -20,7 +20,7 @@ library(quitte)
```{r, echo=FALSE, message=FALSE, warning=FALSE}
# Set RDS files path
EJmode_all = readRDS("EJmode_all.RDS")
EJLDV_all = readRDS("EJLDV_all.RDS")
EJroad_all = readRDS("EJroad_all.RDS")
fleet_all = readRDS("fleet_all.RDS")
salescomp_all = readRDS("salescomp_all.RDS")
ESmodecap_all = readRDS("ESmodecap_all.RDS")
......@@ -182,16 +182,17 @@ salescompf(salescomp_all)
```
```{r, echo=FALSE, message=FALSE, warning=FALSE}
EJLDVpf = function(dt){
EJroadpf = function(dt){
dt[, technology := factor(technology, levels = legend_ord)]
plot = ggplot()+
geom_area(data = dt, aes(x=year, y=demand_EJ, group = technology, fill = technology), color="black",position= position_stack())+
dt = dt[year >= 2020]
plotLDV = ggplot()+
geom_area(data = dt[subsector_L1 == "trn_pass_road_LDV_4W"], aes(x=year, y=demand_EJ, group = technology, fill = technology), color = "black", size=0.05, position= position_stack())+
labs(x = "", y = "[EJ]", title = "LDV Final Energy demand")+
theme_minimal()+
facet_grid(scenario~region)+
scale_fill_manual("Technology", values = cols, breaks=legend_ord)+
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
scale_x_continuous(breaks = c(2020, 2030,2050, 2100))+
theme(axis.text.x = element_text(angle = 90, size = 8, vjust=0.5, hjust=1),
axis.text.y = element_text(size = 8),
axis.title = element_text(size = 8),
......@@ -201,23 +202,63 @@ EJLDVpf = function(dt){
# legend.title = element_text(size = 8),
strip.text = element_text(size=8),
strip.background = element_rect(color = "grey"))
return(plot)
plotBus = ggplot()+
geom_area(data = dt[subsector_L1 %in% c("trn_pass_road_bus_tmp_subsector_L1", "Bus_tmp_subsector_L1")], aes(x=year, y=demand_EJ, group = technology, fill = technology), color = "black", size=0.05, position= position_stack())+
labs(x = "", y = "[EJ]", title = "Buses Final Energy demand")+
theme_minimal()+
facet_grid(scenario~region)+
scale_fill_manual("Technology", values = cols, breaks=legend_ord)+
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2020, 2030,2050, 2100))+
theme(axis.text.x = element_text(angle = 90, size = 8, vjust=0.5, hjust=1),
axis.text.y = element_text(size = 8),
axis.title = element_text(size = 8),
axis.line = element_line(size = 0.5, colour = "grey"),
title = element_text(size = 8),
# legend.text = element_text(size =8),
# legend.title = element_text(size = 8),
strip.text = element_text(size=8),
strip.background = element_rect(color = "grey"))
plotTrucks = ggplot()+
geom_area(data = dt[subsector_L1 %in% c("trn_freight_road_tmp_subsector_L1")], aes(x=year, y=demand_EJ, group = technology, fill = technology), color = "black", size=0.05, position= position_stack())+
labs(x = "", y = "[EJ]", title = "Trucks Final Energy demand")+
theme_minimal()+
facet_grid(scenario~region)+
scale_fill_manual("Technology", values = cols, breaks=legend_ord)+
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2020, 2030,2050, 2100))+
theme(axis.text.x = element_text(angle = 90, size = 8, vjust=0.5, hjust=1),
axis.text.y = element_text(size = 8),
axis.title = element_text(size = 8),
axis.line = element_line(size = 0.5, colour = "grey"),
title = element_text(size = 8),
# legend.text = element_text(size =8),
# legend.title = element_text(size = 8),
strip.text = element_text(size=8),
strip.background = element_rect(color = "grey"))
return(plotlist = list(plotLDV = plotLDV, plotBus = plotBus, plotTrucks = plotTrucks))
}
EJLDVpf(EJLDV_all)
EJroadpf(EJroad_all)
```
```{r, echo=FALSE, message=FALSE, warning=FALSE}
EJmodepf = function(dt){
dt = dt[year >= 2020]
plot = ggplot()+
geom_area(data = dt, aes(x=year, y=demand_EJ, group = interaction(vehicle_type_plot,aggr_mode), fill = vehicle_type_plot), color = "black", position= position_stack())+
geom_area(data = dt, aes(x=year, y=demand_EJ, group = interaction(vehicle_type_plot,aggr_mode), fill = vehicle_type_plot), color = "black", size=0.05, position= position_stack())+
labs(x = "", y = "[EJ]", title = "Total transport final energy demand")+
theme_minimal()+
facet_grid(scenario~region)+
scale_fill_manual("Vehicle Type",values = cols, breaks=legend_ord)+
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
scale_x_continuous(breaks = c(2020,2030,2050, 2100))+
theme(axis.text.x = element_text(angle = 90, size = 8, vjust=0.5, hjust=1),
axis.text.y = element_text(size=8),
axis.title = element_text(size = 8),
......@@ -239,13 +280,13 @@ EJmodepf(EJmode_all)
ESmodecappf = function(dt){
dt[, vehicle_type_plot := factor(vehicle_type_plot, levels = legend_ord)]
plot_frgt = ggplot()+
geom_area(data = dt[mode == "freight"], aes(x=year, y=cap_dem, group = vehicle_type_plot, fill = vehicle_type_plot), color="black",position= position_stack())+
geom_area(data = dt[mode == "freight" & year >= 2020], aes(x=year, y=cap_dem, group = vehicle_type_plot, fill = vehicle_type_plot), color="black", size=0.05, position= position_stack())+
labs(x = "", y = "Energy Services demand [tkm/cap]")+
theme_minimal()+
facet_grid(scenario~region)+
scale_fill_manual("Vehicle Type",values = cols, breaks=legend_ord)+
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
scale_x_continuous(breaks = c(2020,2030,2050, 2100))+
theme(axis.text.x = element_text(angle = 90, size = 8, vjust=0.5, hjust=1),
axis.text.y = element_text(size = 8),
axis.title = element_text(size = 8),
......@@ -258,13 +299,13 @@ ESmodecappf = function(dt){
plot_pass = ggplot()+
geom_area(data = dt[mode == "pass"], aes(x=year, y=cap_dem, group = vehicle_type_plot, fill = vehicle_type_plot), color="black",position= position_stack())+
geom_area(data = dt[mode == "pass" & year >= 2020], aes(x=year, y=cap_dem, group = vehicle_type_plot, fill = vehicle_type_plot), color="black", size=0.05, position= position_stack())+
labs(x = "", y = "Energy Services demand [pkm/cap]")+
theme_minimal()+
facet_grid(scenario~region)+
scale_fill_manual("Vehicle Type",values = cols, breaks=legend_ord)+
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
scale_x_continuous(breaks = c(2020,2030,2050, 2100))+
theme(axis.text.x = element_text(angle = 90, size = 8, vjust=0.5, hjust=1),
axis.text.y = element_text(size = 8),
axis.title = element_text(size = 8),
......@@ -289,10 +330,10 @@ ESmodecappf(ESmodecap_all)
CO2km_int_newsalespf = function(dt){
dt = dt[!is.na(gCO2_km_ave)]
plot = ggplot()+
geom_line(data = dt[year >=2020], aes(x = year, y = gCO2_km_ave, group = scenario, color = scenario))+
geom_line(data = dt[year >= 2020], aes(x = year, y = gCO2_km_ave, group = scenario, color = scenario))+
labs(title = expression(paste(CO["2"], " intensity of LDVs new additions")), y = expression(paste("[", gCO["2"], "/km]")), x = "")+
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
scale_x_continuous(breaks = c(2020, 2030, 2050, 2100))+
theme_minimal()+
facet_grid(~region)+
theme(axis.text.x = element_text(angle = 90, size = 8, vjust=0.5, hjust=1),
......@@ -315,14 +356,15 @@ CO2km_int_newsalespf(CO2km_int_newsales_all)
```{r, echo=FALSE, message=FALSE, warning=FALSE}
## LDV by fuel
EJfuels_pf = function(dt){
dt = dt[year >= 2020]
plot = ggplot()+
geom_area(data = dt, aes(x=year, y=demand_EJ, group = subtech, fill = subtech), color="black", position= position_stack())+
geom_area(data = dt, aes(x=year, y=demand_EJ, group = subtech, fill = subtech), color="black", size=0.05, position= position_stack())+
labs(x = "", y = "[EJ]", title = "Transport FE demand by fuel")+
theme_minimal()+
facet_grid(scenario~region)+
scale_fill_manual("Technology",values = cols, breaks=legend_ord)+
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
scale_x_continuous(breaks = c(2020, 2030,2050, 2100))+
theme(axis.text.x = element_text(angle = 90, size = 8, vjust=0.5, hjust=1),
axis.text.y = element_text(size = 8),
axis.title = element_text(size = 8),
......@@ -341,20 +383,22 @@ EJfuels_pf(EJfuels_all)
```{r, echo=FALSE, message=FALSE, warning=FALSE}
emidem_pf = function(dt){
dt[, scenario := as.character(scenario)]
plot = ggplot()+
geom_line(data = dt, aes(x = year, y = value, group = variable, color = variable))+
labs(x = "", y = "CO2 emissions [Mt/CO2]")+
geom_line(data = dt, aes(x = year, y = value, group = scenario, color = scenario))+
labs(x = "", y = "CO2 emissions [Mt/CO2]", title = "Emissions from transport demand")+
theme_minimal()+
facet_grid(~region)+
theme(axis.text.x = element_text(size = 8),
axis.text.y = element_text(size=8),
axis.title = element_text(size = 9),
title = element_text(size = 9),
legend.position = "none",
strip.text = element_text(size=9))+
scale_color_manual("Scenario", values = cols)
theme(axis.text.x = element_text(angle = 90, size = 8, vjust=0.5, hjust=1),
axis.text.y = element_text(size = 8),
axis.title = element_text(size = 8),
title = element_text(size = 8),
legend.text = element_text(size = 8),
legend.title = element_text(size = 8),
strip.text = element_text(size = 8),
strip.background = element_rect(color = "grey"),
axis.line = element_line(size = 0.5, colour = "grey"))
return(plot)
}
......
scripts/output/comparison/notebook_templates/helper_dashboard.R
+ 3
− 3
View file @ f4bc4159
......@@ -84,7 +84,7 @@ plotlyButtonsToHide <- list('sendDataToCloud', 'zoom2d', 'pan2d', 'select2d', 'l
## Load files
EJmode_all = readRDS("EJmode_all.RDS")
EJLDV_all = readRDS("EJLDV_all.RDS")
EJroad_all = readRDS("EJroad_all.RDS")
fleet_all = readRDS("fleet_all.RDS")
salescomp_all = readRDS("salescomp_all.RDS")
ESmodecap_all = readRDS("ESmodecap_all.RDS")
......@@ -287,7 +287,7 @@ CO2km_intensity_newsalesdash = function(dt, scen){
}
EJLDVdash <- function(dt, scen){
dt = dt[subsector_L1 == "trn_pass_road_LDV_4W"]
dt[, technology := factor(technology, levels = legend_ord)]
dt = dt[region == region_plot & scenario == scen & year >= 2015 & year <= 2050]
dt[, details := paste0("Demand: ", round(demand_EJ, digits = 1), " [EJ]","<br>", "Technology: ", technology, "<br>", "Region: ", region," <br>", "Year: ", year) ]
......@@ -378,7 +378,7 @@ create_plotlist = function(scens, salescomp_all, fleet_all, ESmodecap_all, EJfue
## CO2 intensity new sales LDVs
CO2km_int_newsales = CO2km_intensity_newsalesdash(CO2km_int_newsales_all, scen)
## final energy LDVs by fuel
EJLDV = EJLDVdash(EJLDV_all, scen)
EJLDV = EJLDVdash(EJroad_all, scen)
## emissions transport demand
emidem = emidem_dash(emidem_all, scen)
......
scripts/output/single/notebook_templates/EDGETransportReport.Rmd
+ 20
− 4
View file @ f4bc4159
......@@ -197,7 +197,7 @@ p
plotinconv = function(inco_tech, iso_plot, vehicle_type){
p=ggplot()+
geom_bar(data = inco_tech[iso == iso_plot & subsector_L1 == "trn_pass_road_LDV_4W" & vehicle_type == vehicle_type & year<=2100 & year>=2010], aes(x = as.character(year), y = value, group = logit_type, fill = logit_type), position = position_stack(), stat = "identity")+
facet_grid(~technology)+
facet_wrap(~technology, norw = 3)+
theme_minimal()+
# scale_fill_manual(values = cols)+
expand_limits(y = c(0,0.8))+
......@@ -383,10 +383,25 @@ demandEJplotf = function(demandEJ, POP){
1e-6] ## in people/millionpeople=GJ/person
p=ggplot()+
geom_area(data = demandEJ[year > 2010], aes(x=year, y=demand_EJ, group = interaction(vehicle_type_plot,aggr_mode), fill = vehicle_type_plot), color = "black", position= position_stack())+
ppass=ggplot()+
geom_area(data = demandEJ[year > 2010 & aggr_mode %in% c("LDV", "Pass non LDV")], aes(x=year, y=demand_EJ, group = interaction(vehicle_type_plot,aggr_mode), fill = vehicle_type_plot), color = "black", position= position_stack())+
facet_wrap(~region, nrow = 4)+
labs(x = "", y = "Passenger final Energy demand [EJ]")+
theme_minimal()+
scale_fill_manual(values = cols)+
# scale_fill_manual("Vehicle Type",values = cols, breaks=legend_ord)+
theme(axis.text.x = element_text(size = 8),
axis.text.y = element_text(size=8),
axis.title = element_text(size = 9),
title = element_text(size = 9),
legend.text = element_text(size = 9),
legend.title = element_text(size =9),
strip.text = element_text(size=9))
pfreight=ggplot()+
geom_area(data = demandEJ[year > 2010 & aggr_mode %in% c("Freight")], aes(x=year, y=demand_EJ, group = interaction(vehicle_type_plot,aggr_mode), fill = vehicle_type_plot), color = "black", position= position_stack())+
facet_wrap(~region, nrow = 4)+
labs(x = "", y = "Final Energy demand [EJ]")+
labs(x = "", y = "Freight final Energy demand [EJ]")+
theme_minimal()+
scale_fill_manual(values = cols)+
# scale_fill_manual("Vehicle Type",values = cols, breaks=legend_ord)+
......@@ -398,6 +413,7 @@ demandEJplotf = function(demandEJ, POP){
legend.title = element_text(size =9),
strip.text = element_text(size=9))
pcap=ggplot()+
geom_area(data = demandEJcap[year > 2020], aes(x=year, y=cap_dem, group = interaction(vehicle_type_plot,aggr_mode), fill = vehicle_type_plot), color = "black", position= position_stack())+
facet_wrap(~region, nrow = 4)+
......
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