Merge branch 'main' of github.com:pik-piam/mredgebuildings into uvalues

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '1232870'
+ValidationKey: '1397480'
 AutocreateReadme: yes
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'

.gitignore

@@ -3,29 +3,8 @@
 .RData
 .Ruserdata
 .DS_Store
-R/convertWEO.R
-R/readWEO.R
 inst/extdata/.DS_Store
 inst/extdata/regional/.DS_Store
-inst/extdata/regional/regionmappingEUshares.csv
-inst/extdata/regional/regionmappingIEA_ETP-Shares.csv
-inst/extdata/regional/regionmappingISO-EDGE_EUR_ETP.csv
-inst/extdata/regional/regionmappingWEO.csv
 inst/extdata/sectoral/baitregression-files_test.csv
 inst/regional/
-inst/sectoral/
-man/aggCells.Rd
-man/blend.Rd
-man/calcBAIT.Rd
-man/calcBAITpars.Rd
-man/calcCellHDDCDD.Rd
-man/calcHDDCDDFactors.Rd
-man/calcStackHDDCDD.Rd
-man/cfac.Rd
-man/checkDates.Rd
-man/convertISIMIPbuildings.Rd
-man/convertWEO.Rd
-man/prepBaitInput.Rd
-man/readISIMIPbuildings.Rd
-man/readWEO.Rd
-man/smooth.Rd
+inst/sectoral/

.pre-commit-config.yaml

@@ -15,7 +15,7 @@ repos:
     -   id: mixed-line-ending
 
 -   repo: https://github.com/lorenzwalthert/precommit
-    rev: 7910e0323d7213f34275a7a562b9ef0fde8ce1b9  # frozen: v0.4.2
+    rev: bae853d82da476eee0e0a57960ee6b741a3b3fb7  # frozen: v0.4.3
     hooks:
     -   id: parsable-R
     -   id: deps-in-desc

CITATION.cff

@@ -2,14 +2,14 @@ cff-version: 1.2.0
 message: If you use this software, please cite it using the metadata from this file.
 type: software
 title: 'mredgebuildings: Prepare data to be used by the EDGE-Buildings model'
-version: 0.6.2
-date-released: '2024-06-11'
+version: 0.7.0
+date-released: '2024-08-29'
 abstract: Prepare data to be used by the EDGE-Buildings model.
 authors:
 - family-names: Hasse
   given-names: Robin
   email: robin.hasse@pik-potsdam.de
-  orcid: 0000-0003-1818-3186
+  orcid: https://orcid.org/0000-0003-1818-3186
 - family-names: Führlich
   given-names: Pascal
   email: pascal.fuehrlich@pik-potsdam.de

DESCRIPTION

@@ -1,8 +1,8 @@
 Type: Package
 Package: mredgebuildings
 Title: Prepare data to be used by the EDGE-Buildings model
-Version: 0.6.2
-Date: 2024-06-11
+Version: 0.7.0
+Date: 2024-08-29
 Authors@R: c(
     person("Robin", "Hasse", , "robin.hasse@pik-potsdam.de", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0003-1818-3186")),
@@ -20,11 +20,12 @@ Depends:
     mrcommons (>= 1.35.0),
     mrremind (>= 0.175.4)
 Imports:
-    brick (>= 0.1.3),
+    brick (>= 0.5.0),
     dplyr,
     GDPuc,
     ncdf4,
     openxlsx,
+    purrr,
     plyr,
     pracma,
     raster,
@@ -43,4 +44,4 @@ Suggests:
     testthat
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2

NAMESPACE

@@ -5,6 +5,10 @@ export(calcCarrierPrices)
 export(calcCostConstruction)
 export(calcCostDemolition)
 export(calcCostRenovation)
+export(calcEfficiencyRegression)
+export(calcFEUE)
+export(calcFEUEefficiencies)
+export(calcFEbyEUEC)
 export(calcFEdemandBuildings)
 export(calcFloorspacePast)
 export(calcHeatingCapacity)
@@ -14,10 +18,12 @@ export(calcIEAPFU)
 export(calcIEAfloorspace)
 export(calcLifetimeParams)
 export(calcMatchingReference)
+export(calcPFUDB)
 export(calcPopulationBuildings)
 export(calcRenovationCostModel)
 export(calcShareETP)
 export(calcShareOdyssee)
+export(calcShareTCEP)
 export(calcSharesBuildingDemand)
 export(calcSurface)
 export(calcUEdemand)
@@ -35,6 +41,8 @@ export(convertEurostatBuildings)
 export(convertGDL)
 export(convertHDDCDD)
 export(convertOdyssee)
+export(convertPFUDB)
+export(convertTCEP)
 export(convertUNHouseholds)
 export(fullEDGEBUILDINGS)
 export(getFEbyEUEC)
@@ -55,9 +63,12 @@ export(readGDL)
 export(readHotmaps)
 export(readIEAfloorspace)
 export(readOdyssee)
+export(readPFUDB)
+export(readTCEP)
 export(readUNHouseholds)
 export(toolCountryFillAvg)
 export(toolDisaggregate)
+export(toolSplitBiomass)
 export(toolUnitConversion)
 import(madrat)
 import(magclass)
@@ -86,6 +97,7 @@ importFrom(dplyr,left_join)
 importFrom(dplyr,matches)
 importFrom(dplyr,mutate)
 importFrom(dplyr,n)
+importFrom(dplyr,pull)
 importFrom(dplyr,reframe)
 importFrom(dplyr,relocate)
 importFrom(dplyr,rename)
@@ -122,9 +134,12 @@ importFrom(ncdf4,nc_open)
 importFrom(openxlsx,read.xlsx)
 importFrom(plyr,revalue)
 importFrom(pracma,integral2)
+importFrom(purrr,reduce)
 importFrom(quadprog,solve.QP)
+importFrom(quitte,aggregate_map)
 importFrom(quitte,as.quitte)
 importFrom(quitte,calc_addVariable)
+importFrom(quitte,factor.data.frame)
 importFrom(quitte,getPeriods)
 importFrom(quitte,getRegs)
 importFrom(quitte,inline.data.frame)
@@ -133,8 +148,12 @@ importFrom(quitte,removeColNa)
 importFrom(quitte,replace_column)
 importFrom(quitte,revalue.levels)
 importFrom(raster,writeRaster)
+importFrom(readxl,read_excel)
 importFrom(readxl,read_xlsx)
 importFrom(rlang,.data)
+importFrom(rlang,syms)
+importFrom(stats,SSasymp)
+importFrom(stats,as.formula)
 importFrom(stats,coef)
 importFrom(stats,dnorm)
 importFrom(stats,lm)
@@ -160,6 +179,7 @@ importFrom(terra,writeCDF)
 importFrom(tidyr,"%>%")
 importFrom(tidyr,complete)
 importFrom(tidyr,gather)
+importFrom(tidyr,one_of)
 importFrom(tidyr,pivot_longer)
 importFrom(tidyr,pivot_wider)
 importFrom(tidyr,replace_na)

R/calcCarrierPrices.R

@@ -61,16 +61,9 @@ calcCarrierPrices <- function() {
 
   # map ECEMF carriers
   # assumption: liquids and gases remain fossil
-  carrierMap <- inline.data.frame(
-    "carrierECEMF;       carrier",
-    "Gases - Fossil Gas; gases",
-    "Liquids - Oil;      liquids",
-    "Liquids - Biomass;  NA",
-    "Electricity;        elec",
-    "Hydrogen;           NA",
-    "Solids - Coal;      coal",
-    "Solids - Biomass;   biomod"
-  )
+  carrierMap <- toolGetMapping("carrierMapping_ECEMF.csv",
+                               type = "sectoral",
+                               where = "mredgebuildings")
 
   # all considered price components
   # (drop CO2 price as this is a scenario assumption)
@@ -186,7 +179,17 @@ calcCarrierPrices <- function() {
 
   # Combine data ---------------------------------------------------------------
 
-  data <- rbind(prices, emi) %>%
+  data <- rbind(prices, emi)
+
+  # all carriers included?
+  carrier <- unique(getBrickMapping("heatingSystem.csv")["carrier"])
+  data <- data %>%
+    right_join(carrier, by = "carrier")
+  if (any(is.na(data))) {
+    stop("Incomplete mapping of energy carriers.")
+  }
+
+  data <- data  %>%
     as.quitte() %>%
     as.magpie()
 

R/calcCostRenovation.R

@@ -40,7 +40,7 @@ calcCostRenovation <- function(energyLadder = FALSE) {
   ## Heating mark down ====
 
   # decrease installation cost if there is no technology switch
-  sameHsFactor <- 0.9
+  sameHsFactor <- 0.2
 
 
 
@@ -137,7 +137,7 @@ calcCostRenovation <- function(energyLadder = FALSE) {
     as.quitte(na.rm = TRUE) %>%
     select("region", "typ", "vin", "bs", capacity = "value")
 
-  # heating system installation cost: USD/kW -> USD/m2
+  # heating system purchasing cost: USD/kW -> USD/m2
   heatingCost <- calcOutput("HeatingSystem",
                             subtype = "Purchasing cost",
                             aggregate = FALSE) %>%
@@ -157,19 +157,38 @@ calcCostRenovation <- function(energyLadder = FALSE) {
                              .data[["hsr"]])) %>%
     left_join(heatingCost, by = c(hs.final = "hs"),
               relationship = "many-to-many") %>%
-    mutate(heatingCost = ifelse(.data[["hs"]] == .data[["hsr"]],
-                                sameHsFactor * .data[["heatingCost"]],
-                                ifelse(.data[["hsr"]] == "0",
-                                       0,
-                                       .data[["heatingCost"]]))) %>%
+    mutate(heatingCost = ifelse(.data[["hsr"]] == "0",
+                                0,
+                                .data[["heatingCost"]])) %>%
     select(-"hs.final")
 
+  # heating system installation cost (independent of capacity)
+  # rough numbers from BDEW Heizkostenvergleich cost/floor
+  installationCost <- inline.data.frame(
+    "typ; installationCost",
+    "SFH; 30",
+    "MFH; 10",
+    "Com; 6"
+  )
+  heatingCost <- heatingCost %>%
+    left_join(installationCost, by = "typ") %>%
+    mutate(installationCost = .data[["installationCost"]] *
+             ifelse(.data[["hsr"]] == "0",
+                    0,
+                    ifelse(.data[["hsr"]] == "reel",
+                           0.1,
+                           ifelse(.data[["hs"]] == .data[["hsr"]],
+                                  sameHsFactor,
+                                  1))),
+           heatingCost = .data[["heatingCost"]] + .data[["installationCost"]]) %>%
+    select(-"installationCost")
+
   # mark up for installation of central heating system (piping, etc.)
   # https://www.checkatrade.com/blog/cost-guides/central-heating-installation-cost/
   heatingCost <- heatingCost %>%
     mutate(heatingCost = .data[["heatingCost"]] +
              ifelse(.data[["hs"]] == "reel" & !.data[["hsr"]] %in% c("0", "reel"),
-                    3000 / 150 * 1.21, # units GBP/m2 * USD/GBP
+                    3000 / 150 * 1.21, # units: GBP / m2 * USD/GBP # nolint: commented_code_linter.
                     0))
 
   ## Total ====

R/calcDensity.R

@@ -0,0 +1,69 @@
+#' Get Population Density
+#'
+#' @returns magpie object
+#'
+#' @author Hagen Tockhorn
+#'
+#' @importFrom madrat calcOutput
+#' @importFrom dplyr select mutate rename
+#' @importFrom quitte as.quitte
+#' @importFrom magclass as.magpie
+
+
+calcDensity <- function() {
+
+  # READ-IN DATA----------------------------------------------------------------
+
+  pop <- calcOutput("PopulationPast", aggregate = FALSE) %>%
+    as.quitte()
+
+  surf <- calcOutput("Surface", aggregate = FALSE) %>%
+    as.quitte()
+
+
+  # PARAMETERS------------------------------------------------------------------
+
+  # Conversion from 1-e6 --> 1e0
+  million2unit <- 1e6
+
+
+  # PROCESS DATA----------------------------------------------------------------
+
+  # Clean DFs
+  pop <- pop %>%
+    select(-"model", -"scenario", -"unit", -"variable") %>%
+    mutate(value = .data[["value"]] * million2unit) %>%
+    rename(population = "value")
+
+  surf <- surf %>%
+    select(-"model", -"scenario", -"unit", -"variable", -"period") %>%
+    rename(surface = "value")
+
+  # Calculate Density
+  dens <- left_join(pop, surf, by = "region") %>%
+    mutate(value = .data[["population"]] / (.data[["surface"]] * 1e3)) %>%
+    select(-"population", -"surface")
+
+
+  # Fill inf values with global density average
+  avgDens <- mean(dens[!is.infinite(dens$value), ]$value)
+
+  dens <- dens %>%
+    mutate(value = ifelse(is.infinite(.data[["value"]]),
+                          avgDens,
+                          .data[["value"]]))
+
+
+
+  # OUTPUT----------------------------------------------------------------------
+
+  data <- dens %>%
+    as.data.frame() %>%
+    as.quitte() %>%
+    as.magpie()
+
+  return(list(x = data,
+              weight = NULL,
+              unit = "m^-2",
+              description = "Population Density in m^-2"))
+}