Adjust NAVIGATE scenarios

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '2556190'
+ValidationKey: '2756880'
 AutocreateReadme: yes
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'

.github/workflows/check.yaml

@@ -23,6 +23,7 @@ jobs:
       - uses: r-lib/actions/setup-r-dependencies@v2
         with:
           extra-packages: |
+            gamstransfer=?ignore
             any::lucode2
             any::covr
             any::madrat

.pre-commit-config.yaml

@@ -3,7 +3,7 @@
 exclude: '^tests/testthat/_snaps/.*$'
 repos:
 -   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v4.5.0
     hooks:
     -   id: check-case-conflict
     -   id: check-json
@@ -15,7 +15,7 @@ repos:
     -   id: mixed-line-ending
 
 -   repo: https://github.com/lorenzwalthert/precommit
-    rev: v0.3.2.9021
+    rev: v0.3.2.9025
     hooks:
     -   id: parsable-R
     -   id: deps-in-desc

CITATION.cff

@@ -2,8 +2,8 @@ cff-version: 1.2.0
 message: If you use this software, please cite it using the metadata from this file.
 type: software
 title: 'edgeTransport: Prepare EDGE Transport Data for the REMIND model'
-version: 1.3.0
-date-released: '2023-11-02'
+version: 1.4.0
+date-released: '2023-12-01'
 abstract: EDGE-T is a fork of the GCAM transport module https://jgcri.github.io/gcam-doc/energy.html#transportation
   with a high level of detail in its representation of technological and modal options.
   It is a partial equilibrium model with a nested multinomial logit structure and

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: edgeTransport
 Title: Prepare EDGE Transport Data for the REMIND model
-Version: 1.3.0
+Version: 1.4.0
 Authors@R: c(
     person("Alois", "Dirnaichner", email = "[email protected]", role = c("aut", "cre")),
     person("Marianna", "Rottoli", email = "[email protected]", role = "aut"),
@@ -15,7 +15,7 @@ Encoding: UTF-8
 LazyData: true
 RoxygenNote: 7.2.3
 VignetteBuilder: knitr
-Date: 2023-11-02
+Date: 2023-12-01
 Config/testthat/edition: 3
 Imports:
     rmndt,

R/incotrend.R

@@ -294,7 +294,7 @@ Hybrid Electric,Liquids")
       FVtarget_tb[, value := ifelse(year==2035,0.3*value[year==2015],value),by = c("region","technology")]
       FVtarget_tb[, value := ifelse(year==2040,0.2*value[year==2015],value),by = c("region","technology")]
       FVtarget_tb[, value := ifelse(year==2045,0.1*value[year==2015],value),by = c("region","technology")]
-      FVtarget_tb[year>=2045, value := 0.05]
+      FVtarget_tb[year > 2045, value := value * 0.05]
 
       FVtarget=rbind(FVtarget_all,FVtarget_tb)
 
@@ -316,6 +316,23 @@ Hybrid Electric,Liquids")
 
       FVtarget=rbind(FVtarget_all,FVtarget_tb)
 
+    } else if (tech_scen %in% c("NAV_all", "NAV_ele")) {
+
+      FVtarget_all = FVtarget[!(technology %in% c("Liquids","NG") & subsector_L1 %in% c("trn_freight_road_tmp_subsector_L1", "Bus_tmp_subsector_L1"))]
+
+      FVtarget_all[, value := ifelse(
+        is.na(target), value, apply_logistic_trends(year, target, symmyr, speed) * value),
+        by=c("region", "vehicle_type", "technology")]
+
+      ## ICE trucks and buses
+      FVtarget_tb = FVtarget[subsector_L1 %in% c("trn_freight_road_tmp_subsector_L1", "Bus_tmp_subsector_L1") & technology %in% c("Liquids", "NG")]
+      FVtarget_tb[, value := ifelse(year==2025,0.6*value[year==2015],value),by = c("region","technology")]
+      FVtarget_tb[, value := ifelse(year==2030,0.3*value[year==2015],value),by = c("region","technology")]
+      FVtarget_tb[, value := ifelse(year==2035,0.1*value[year==2015],value),by = c("region","technology")]
+      FVtarget_tb[year >= 2040, value := 0]
+
+      FVtarget=rbind(FVtarget_all,FVtarget_tb)
+
     } else {
 
       FVtarget[, value := ifelse(

R/logit.R

@@ -573,7 +573,7 @@ toolCalculateLogitIncost <- function(prices,
                                                      0.5*exp(1)^(weighted_sharessum[year == (t-1)]*bmodelav),
                                                      pinco_tot), by = c("region", "technology", "vehicle_type", "subsector_L1")]
 
-    if(tech_scen %in% c("PhOP", "Mix3", "Mix4", "HydrHype4", "ECEMF_HighEl_ModEff", "ECEMF_HighEl_HighEff", "ECEMF_HighEl_LifestCha", "ECEMF_HighH2_ModEff", "ECEMF_HighH2_HighEff", "ECEMF_HighH2_LifestCha", "CAMP_lscWeak", "CAMP_lscStrong") & t>= 2030){
+    if(tech_scen %in% c("PhOP", "Mix3", "Mix4", "HydrHype4", "ECEMF_HighEl_ModEff", "ECEMF_HighEl_HighEff", "ECEMF_HighEl_LifestCha", "ECEMF_HighH2_ModEff", "ECEMF_HighH2_HighEff", "ECEMF_HighH2_LifestCha", "CAMP_lscWeak", "CAMP_lscStrong", "NAV_all", "NAV_ele") & t>= 2030){
       ## phase-out of all light-duty vehicle ICEs
       EUreg <- c("DEU", "ECE", "ECS", "ENC", "ESC", "ESW", "EWN", "FRA", "UKI", "EUR")
 
@@ -583,33 +583,62 @@ toolCalculateLogitIncost <- function(prices,
         floorEU <- linIncrease(t, 2032, 0.35, 2034, 0.95)
       } else if (t== 2035){
         floorEU <- 0.95
-      } else {
+      } else if (t > 2035){
         floorEU <- 1
       }
 
+      if(t > 2035 & t <= 2037){
+        floorGLO <- linIncrease(t, 2035, floor, 2037, 0.15)
+      } else if(t > 2037 & t <= 2039){
+        floorGLO <- linIncrease(t, 2037, 0.15, 2039, 1.6)
+      } else if (t == 2040){
+        floorGLO <- 2
+      } else if (t > 2040){
+        floorGLO <- 2.2
+      }
+
+
       tmp[technology == "Liquids" & region %in% EUreg, pinco_tot := ifelse(year == t,
                                                                            pmax(pinco_tot, floorEU),
                                                                            pinco_tot), by = c("region", "technology", "vehicle_type", "subsector_L1")]
 
-      tmp[technology == "Liquids"  & !region %in% EUreg, pinco_tot := ifelse(year == t,
-                                                                             pmax(pinco_tot, floor),
-                                                                             pinco_tot), by = c("region", "technology", "vehicle_type", "subsector_L1")]
+      tmp[technology == "Hybrid Electric" & region %in% EUreg, pmod_av := ifelse(year == t,
+                                                                                 pmax(pmod_av, floorEU),
+                                                                                pmod_av), by = c("region", "technology", "vehicle_type", "subsector_L1")]
 
       tmp[technology == "NG" & region %in% EUreg, pref := ifelse(year == t,
                                                                  pmax(pref, floorEU),
                                                                  pref), by = c("region", "technology", "vehicle_type", "subsector_L1")]
 
-      tmp[technology == "Hybrid Electric" & region %in% EUreg, pmod_av := ifelse(year == t,
-                                                                                 pmax(pmod_av, floorEU),
-                                                                                 pmod_av), by = c("region", "technology", "vehicle_type", "subsector_L1")]
+          if (tech_scen %in% c("NAV_all", "NAV_ele") & t > 2035){
+            tmp[technology == "Liquids"  & !region %in% EUreg, pinco_tot := ifelse(year == t,
+                                                                                 pmax(pinco_tot, floorGLO),
+                                                                                 pinco_tot), by = c("region", "technology", "vehicle_type", "subsector_L1")]
 
-    } else {
+            tmp[technology == "NG" & !region %in% EUreg, pref := ifelse(year == t,
+                                                                       pmax(pref, floorGLO),
+                                                                       pref), by = c("region", "technology", "vehicle_type", "subsector_L1")]
 
-      tmp[technology == "Liquids", pinco_tot := ifelse(year == t,
+            tmp[technology == "Hybrid Electric" & !region %in% EUreg, pmod_av := ifelse(year == t,
+                                                                                       pmax(pmod_av, floorGLO),
+                                                                                       pmod_av), by = c("region", "technology", "vehicle_type", "subsector_L1")]
+
+
+          } else {
+            tmp[technology == "Liquids"  & !region %in% EUreg, pinco_tot := ifelse(year == t,
+                                                                                   pmax(pinco_tot, floor),
+                                                                                   pinco_tot), by = c("region", "technology", "vehicle_type", "subsector_L1")]
+
+          }
+
+
+      } else {
+
+        tmp[technology == "Liquids", pinco_tot := ifelse(year == t,
                                                        pmax(pinco_tot, floor),
                                                        pinco_tot), by = c("region", "technology", "vehicle_type", "subsector_L1")]
 
-    }
+      }
 
 
     ## hybrid electric inconvenience cost cannot decrease below 50% of 2020 value
@@ -689,7 +718,7 @@ toolCalculateLogitIncost <- function(prices,
   df_shares[, tot_VOT_price:=0]
 
   ## merge value of time for the selected level and assign 0 to the entries that don't have it
-  df <- merge(df, value_time, by=intersect(names(df),names(value_time)), all.x=TRUE)
+  df <- merge(df, value_time, by=intersect(names(df),names(value_time)), all.x = TRUE)
   df <- df[is.na(time_price), time_price := 0]
   df <- df[, tot_VOT_price := time_price]
   df <- df[, tot_price := tot_price + time_price]

README.md

@@ -1,6 +1,6 @@
 # Prepare EDGE Transport Data for the REMIND model
 
-R package **edgeTransport**, version **1.3.0**
+R package **edgeTransport**, version **1.4.0**
 
 [![CRAN status](https://www.r-pkg.org/badges/version/edgeTransport)](https://cran.r-project.org/package=edgeTransport)  [![R build status](https://github.com/pik-piam/edgeTransport/workflows/check/badge.svg)](https://github.com/pik-piam/edgeTransport/actions) [![codecov](https://codecov.io/gh/pik-piam/edgeTransport/branch/master/graph/badge.svg)](https://app.codecov.io/gh/pik-piam/edgeTransport) [![r-universe](https://pik-piam.r-universe.dev/badges/edgeTransport)](https://pik-piam.r-universe.dev/builds)
 
@@ -46,7 +46,7 @@ In case of questions / problems please contact Alois Dirnaichner <dirnaichner@pi
 
 To cite package **edgeTransport** in publications use:
 
-Dirnaichner A, Rottoli M, Hoppe J (2023). _edgeTransport: Prepare EDGE Transport Data for the REMIND model_. R package version 1.3.0, <https://github.com/pik-piam/edgeTransport>.
+Dirnaichner A, Rottoli M, Hoppe J (2023). _edgeTransport: Prepare EDGE Transport Data for the REMIND model_. R package version 1.4.0, <https://github.com/pik-piam/edgeTransport>.
 
 A BibTeX entry for LaTeX users is
 
@@ -55,7 +55,7 @@ A BibTeX entry for LaTeX users is
   title = {edgeTransport: Prepare EDGE Transport Data for the REMIND model},
   author = {Alois Dirnaichner and Marianna Rottoli and Johanna Hoppe},
   year = {2023},
-  note = {R package version 1.3.0},
+  note = {R package version 1.4.0},
   url = {https://github.com/pik-piam/edgeTransport},
 }
 ```

inst/extdata/inconv_factor.csv

@@ -593,20 +593,20 @@ SSP2EU,NAV_tec,targetValICE,0
 SSP2EU,NAV_tec,ratioPHEV,0.5
 SSP2EU,NAV_ele,startYeBEV,2025
 SSP2EU,NAV_ele,startValBEV,0.5
-SSP2EU,NAV_ele,targetYeBEV,2030
+SSP2EU,NAV_ele,targetYeBEV,2035
 SSP2EU,NAV_ele,targetValBEV,0
-SSP2EU,NAV_ele,startYeICE,2020
-SSP2EU,NAV_ele,targetYeICE,2027
-SSP2EU,NAV_ele,targetValICE,0.1
-SSP2EU,NAV_ele,ratioPHEV,0.3
+SSP2EU,NAV_ele,startYeICE,2023
+SSP2EU,NAV_ele,targetYeICE,2055
+SSP2EU,NAV_ele,targetValICE,1.5
+SSP2EU,NAV_ele,ratioPHEV,1.5
 SSP2EU,NAV_all,startYeBEV,2025
 SSP2EU,NAV_all,startValBEV,0.5
-SSP2EU,NAV_all,targetYeBEV,2030
+SSP2EU,NAV_all,targetYeBEV,2035
 SSP2EU,NAV_all,targetValBEV,0
-SSP2EU,NAV_all,startYeICE,2020
-SSP2EU,NAV_all,targetYeICE,2027
-SSP2EU,NAV_all,targetValICE,0.1
-SSP2EU,NAV_all,ratioPHEV,0.3
+SSP2EU,NAV_all,startYeICE,2023
+SSP2EU,NAV_all,targetYeICE,2055
+SSP2EU,NAV_all,targetValICE,1.5
+SSP2EU,NAV_all,ratioPHEV,1.5
 SSP2EU,NAV_lce,startYeBEV,2025
 SSP2EU,NAV_lce,startValBEV,0.5
 SSP2EU,NAV_lce,targetYeBEV,2035