From c131b93ae2d4afe11cc2c033ee762b3a4bfa98f1 Mon Sep 17 00:00:00 2001 From: Falk Benke Date: Tue, 3 Sep 2024 09:44:43 +0200 Subject: [PATCH] remove pcc and pco from 'calcCoolingSharesAll' --- R/calcCoolingSharesAll.R | 67 +++---- R/calcCoolingSharesBase.R | 166 +++++++++--------- R/calcCoolingSharesFuture.R | 166 ++++++++++-------- R/calcWaterConsCoef.R | 3 +- .../sectoral/techmappingDaviesToREMIND.csv | 70 ++++++++ ...ND.csv => techmappingMacknickToREMIND.csv} | 0 6 files changed, 282 insertions(+), 190 deletions(-) create mode 100644 inst/extdata/sectoral/techmappingDaviesToREMIND.csv rename inst/extdata/sectoral/{mappingMacknicktoREMIND.csv => techmappingMacknickToREMIND.csv} (100%) diff --git a/R/calcCoolingSharesAll.R b/R/calcCoolingSharesAll.R index f773aa04..23cf7107 100644 --- a/R/calcCoolingSharesAll.R +++ b/R/calcCoolingSharesAll.R @@ -1,5 +1,5 @@ #' Calculate Cooling Type Shares -#' +#' #' This function merges the output of two other functions that calculate REMIND #' input data for the shares of cooling types per electricity technology and #' REMIND region, using as initial information the Davies (2013) data per @@ -7,8 +7,8 @@ #' calculate data for the base year and for future time steps. The source data #' provide most required information but some assumptions on missing data are #' also made. -#' -#' +#' +#' #' @return MAgPIE object on cooling type shares per elecricity technology and #' REMIND region #' @author Ioanna Mouratiadou @@ -16,40 +16,43 @@ #' \code{\link{convertDaviesCooling}}, #' \code{\link{calcCoolingSharesBase}},\code{\link{calcCoolingSharesFuture}} #' @examples -#' -#' \dontrun{ -#' +#' \dontrun{ +#' #' a <- calcOutput("CoolingSharesAll") -#' #' } -#' +#' calcCoolingSharesAll <- function() { + cooloutputBase <- calcOutput("CoolingSharesBase", aggregate = FALSE) + cooloutputFuture <- calcOutput("CoolingSharesFuture", aggregate = FALSE) - cooloutputBase <- calcOutput("CoolingSharesBase", aggregate=FALSE) - cooloutputFuture <- calcOutput("CoolingSharesFuture",aggregate=FALSE) - # merge two datasets - outputAll <- mbind(cooloutputBase,cooloutputFuture) - - #assign aggregation weight - weight <- dimSums(calcOutput("IO",subtype="output",aggregate=FALSE)[,2010,c("feelb","feeli")],dim=3) - - #set weights to zero for countries that were not contained in the GCAM2ISO mapping - weight["ALA",,] <- 0 - weight["ATA",,] <- 0 - weight["BES",,] <- 0 - weight["BLM",,] <- 0 - weight["CUW",,] <- 0 - weight["GGY",,] <- 0 - weight["IMN",,] <- 0 - weight["JEY",,] <- 0 - weight["MAF",,] <- 0 - weight["PSE",,] <- 0 - weight["SSD",,] <- 0 - weight["SXM",,] <- 0 + outputAll <- mbind(cooloutputBase, cooloutputFuture) - return(list(x=outputAll, weight=weight, - unit="% of cooling type technologies", - description="Cooling shares for different cooling technologies based on Davies et al. (2013) publication and using electricity use weights (aggregated based on IEA World Energy Balances, 2014) for regional mapping" + # assign aggregation weight + weight <- dimSums(calcOutput("IO", subtype = "output", aggregate = FALSE)[, 2010, c("feelb", "feeli")], dim = 3) + + # set weights to zero for countries that were not contained in the GCAM2ISO mapping + weight["ALA", , ] <- 0 + weight["ATA", , ] <- 0 + weight["BES", , ] <- 0 + weight["BLM", , ] <- 0 + weight["CUW", , ] <- 0 + weight["GGY", , ] <- 0 + weight["IMN", , ] <- 0 + weight["JEY", , ] <- 0 + weight["MAF", , ] <- 0 + weight["PSE", , ] <- 0 + weight["SSD", , ] <- 0 + weight["SXM", , ] <- 0 + + return(list( + x = outputAll, + weight = weight, + unit = "% of cooling type technologies", + description = c( + "Cooling shares for different cooling technologies based on ", + "Davies et al. (2013) publication and using electricity use weights (aggregated ", + "based on IEA World Energy Balances, 2014) for regional mapping" + ) )) } diff --git a/R/calcCoolingSharesBase.R b/R/calcCoolingSharesBase.R index fcb2a046..07d3f511 100644 --- a/R/calcCoolingSharesBase.R +++ b/R/calcCoolingSharesBase.R @@ -1,12 +1,12 @@ #' Calculate Cooling Type Shares for the Base Year -#' +#' #' This function calculates REMIND input data for the shares of cooling types #' per electricity technology and REMIND region in 2005, using as initial #' information the Davies (2013) data per electricity technology and GCAM #' region. The source data provide most required information but some #' assumptions on missing data are also made. -#' -#' +#' +#' #' @return MAgPIE object on cooling type shares per elecricity technology and #' REMIND region #' @author Lavinia Baumstark, Ioanna Mouratiadou @@ -14,105 +14,111 @@ #' \code{\link{convertDaviesCooling}}, #' \code{\link{calcCoolingSharesAll}},\code{\link{calcCoolingSharesFuture}} #' @examples -#' -#' \dontrun{ +#' \dontrun{ #' a <- calcOutput("CoolingSharesBase") #' } -#' @importFrom readxl read_excel - - - calcCoolingSharesBase <- function() { - # read in data - data <- readSource("DaviesCooling", subtype="dataBase") - getNames(data)[grepl("^Sea",getNames(data))] <- "Sea.NA" - + data <- readSource("DaviesCooling", subtype = "dataBase") + getNames(data)[grepl("^Sea", getNames(data))] <- "Sea.NA" + # seperate data for Sea water - Sea <- data[,,"Sea"] - data <- data[,,-which(getNames(data)=="Sea.NA")] - - id <- getNames(data,dim=1) - + Sea <- data[, , "Sea"] + data <- data[, , -which(getNames(data) == "Sea.NA")] + + id <- getNames(data, dim = 1) + # calculate pond - pond <- new.magpie(getRegions(data),getYears(data),id) + pond <- new.magpie(getRegions(data), getYears(data), id) for (i in id) { - pond[,,i] <- 100 - dimSums(data[,,i],dim=3.2) + pond[, , i] <- 100 - dimSums(data[, , i], dim = 3.2) } - getNames(pond) <- paste(getNames(pond),"Pond",sep=".") - + getNames(pond) <- paste(getNames(pond), "Pond", sep = ".") + # add pond to data - data <- mbind(data,pond) - + data <- mbind(data, pond) + # calculate sea water - sea_new <- new.magpie(getRegions(data),getYears(data),id) + sea_new <- new.magpie(getRegions(data), getYears(data), id) for (i in id) { - sea_new[,,i] <- data[,,paste(i,"1-thru",sep=".")] * Sea/100 + sea_new[, , i] <- data[, , paste(i, "1-thru", sep = ".")] * Sea / 100 } - getNames(sea_new) <- paste(getNames(sea_new),"Sea",sep=".") - + getNames(sea_new) <- paste(getNames(sea_new), "Sea", sep = ".") + # correct 1-thru-data - data[,,"1-thru"] <- data[,,"1-thru"] * (1 - Sea/100) + data[, , "1-thru"] <- data[, , "1-thru"] * (1 - Sea / 100) # add sea data to data - data <- mbind(data,sea_new) - + data <- mbind(data, sea_new) + # check if all categories sum up to 100% - check <- new.magpie(getRegions(data),getYears(data),id) + check <- new.magpie(getRegions(data), getYears(data), id) for (i in id) { - check[,,i] <- dimSums(data[,,i],dim=3.2) + check[, , i] <- dimSums(data[, , i], dim = 3.2) } - if(!all(check==100)) { stop("sum of categorie XXX is not 100%")} - + if (!all(check == 100)) { + stop("sum of categorie XXX is not 100%") + } + # read in mapping to REMIND technologies - map_table <- read_excel(toolGetMapping(type = "sectoral", - name = "TechnologyMappingDavies2REMIND.xlsx", - returnPathOnly = TRUE, where = "mappingfolder")) + map_table <- toolGetMapping( + type = "sectoral", + name = "techmappingDaviesToREMIND.csv", + where = "mrremind" + ) map <- list() - map$davies <- paste(map_table$'Davies Source/Technology',map_table$'Davies Cooling',sep=".") - map$remind <- paste(map_table$'REMIND Technology',map_table$'REMIND Cooling',sep=".") - + map$davies <- paste(map_table$Davies.Source.Technology, map_table$Davies.Cooling, sep = ".") + map$remind <- paste(map_table$REMIND.Technology, map_table$REMIND.Cooling, sep = ".") + # calculate REMIND input in REMIND categories - output <- new.magpie(getRegions(data),getYears(data),map$remind) - output[,,] <- 0 - for(d in 1:length(map$davies)){ - if( !map$davies[d] == "-.-"){ - output[,,map$remind[d]] <- data[,,map$davies[d]] + output <- new.magpie(getRegions(data), getYears(data), map$remind) + output[, , ] <- 0 + for (d in 1:length(map$davies)) { + if (!map$davies[d] == "-.-") { + output[, , map$remind[d]] <- data[, , map$davies[d]] } } - + + # remove no longer used technologies pcc and pco + output <- output[, , c("pcc", "pco"), invert = TRUE] + # add assumed data - output[,,"geohdr.tower"] <- 70 - output[,,"geohdr.dry"] <- 20 - output[,,"geohdr.hybrid"] <- 10 - output[,,"hydro.default"] <- 100 - output[,,"wind.default"] <- 100 - output[,,"spv.default"] <- 100 - output[,,"csp.tower"] <- 70 - output[,,"csp.dry"] <- 20 - output[,,"csp.hybrid"] <- 10 - - outputBase <- new.magpie(getRegions(output),c(2005),getNames(output)) - outputBase[,,] <- output[,,] - - #assign aggregation weight - weight <- dimSums(calcOutput("IO",subtype="output",aggregate=FALSE)[,2010,c("feelb","feeli")],dim=3) - - #set weights to zero for countries that were not contained in the GCAM2ISO mapping - weight["ALA",,] <- 0 - weight["ATA",,] <- 0 - weight["BES",,] <- 0 - weight["BLM",,] <- 0 - weight["CUW",,] <- 0 - weight["GGY",,] <- 0 - weight["IMN",,] <- 0 - weight["JEY",,] <- 0 - weight["MAF",,] <- 0 - weight["PSE",,] <- 0 - weight["SSD",,] <- 0 - weight["SXM",,] <- 0 - - return(list(x=outputBase,weight=weight, - unit="% of cooling type technologies", - description="Cooling shares for different cooling technologies based on Davies et al. (2013) publication and using electricity use weights (aggregated based on IEA World Energy Balances, 2014) for regional mapping" + output[, , "geohdr.tower"] <- 70 + output[, , "geohdr.dry"] <- 20 + output[, , "geohdr.hybrid"] <- 10 + output[, , "hydro.default"] <- 100 + output[, , "wind.default"] <- 100 + output[, , "spv.default"] <- 100 + output[, , "csp.tower"] <- 70 + output[, , "csp.dry"] <- 20 + output[, , "csp.hybrid"] <- 10 + + outputBase <- new.magpie(getRegions(output), c(2005), getNames(output)) + outputBase[, , ] <- output[, , ] + + # assign aggregation weight + weight <- dimSums(calcOutput("IO", subtype = "output", aggregate = FALSE)[, 2010, c("feelb", "feeli")], dim = 3) + + # set weights to zero for countries that were not contained in the GCAM2ISO mapping + weight["ALA", , ] <- 0 + weight["ATA", , ] <- 0 + weight["BES", , ] <- 0 + weight["BLM", , ] <- 0 + weight["CUW", , ] <- 0 + weight["GGY", , ] <- 0 + weight["IMN", , ] <- 0 + weight["JEY", , ] <- 0 + weight["MAF", , ] <- 0 + weight["PSE", , ] <- 0 + weight["SSD", , ] <- 0 + weight["SXM", , ] <- 0 + + return(list( + x = outputBase, weight = weight, + unit = "% of cooling type technologies", + description = c( + "Cooling shares for different cooling technologies based on Davies et al. (2013) ", + "publication and using electricity use weights (aggregated based on IEA World ", + "Energy Balances, 2014) for regional mapping" + ) )) } diff --git a/R/calcCoolingSharesFuture.R b/R/calcCoolingSharesFuture.R index c2d71f96..a05576bd 100644 --- a/R/calcCoolingSharesFuture.R +++ b/R/calcCoolingSharesFuture.R @@ -1,12 +1,12 @@ #' Calculate Cooling Type Shares for Future Timesteps -#' +#' #' This function calculates REMIND input data for the shares of cooling types #' per electricity technology and REMIND region in post-2020, using as initial #' information the Davies (2013) data per electricity technology and GCAM #' region. The source data provide most required information but some #' assumptions on missing data are also made. -#' -#' +#' +#' #' @return MAgPIE object on cooling type shares per elecricity technology and #' REMIND region #' @author Ioanna Mouratiadou @@ -14,103 +14,115 @@ #' \code{\link{convertDaviesCooling}}, #' \code{\link{calcCoolingSharesAll}},\code{\link{calcCoolingSharesBase}} #' @examples -#' -#' \dontrun{ +#' \dontrun{ #' a <- calcOutput("CoolingSharesFuture") -#' #' } #' @importFrom readxl read_excel -#' +#' calcCoolingSharesFuture <- function() { - # read in data - data <- readSource("DaviesCooling", subtype="dataFuture") - getNames(data)[grepl("^Sea",getNames(data))] <- "Sea.NA" - + data <- readSource("DaviesCooling", subtype = "dataFuture") + getNames(data)[grepl("^Sea", getNames(data))] <- "Sea.NA" + # seperate data for Sea water - Sea <- data[,,"Sea"] - data <- data[,,-which(getNames(data)=="Sea.NA")] - - id <- getNames(data,dim=1) - + Sea <- data[, , "Sea"] + data <- data[, , -which(getNames(data) == "Sea.NA")] + + id <- getNames(data, dim = 1) + # calculate pond - pond <- new.magpie(getRegions(data),getYears(data),id) + pond <- new.magpie(getRegions(data), getYears(data), id) for (i in id) { - pond[,,i] <- 100 - dimSums(data[,,i],dim=3.2) + pond[, , i] <- 100 - dimSums(data[, , i], dim = 3.2) } - getNames(pond) <- paste(getNames(pond),"Pond",sep=".") - + getNames(pond) <- paste(getNames(pond), "Pond", sep = ".") + # add pond to data - data <- mbind(data,pond) - + data <- mbind(data, pond) + # calculate sea water - sea_new <- new.magpie(getRegions(data),getYears(data),id) + sea_new <- new.magpie(getRegions(data), getYears(data), id) for (i in id) { - sea_new[,,i] <- data[,,paste(i,"1-thru",sep=".")] * Sea/100 + sea_new[, , i] <- data[, , paste(i, "1-thru", sep = ".")] * Sea / 100 } - getNames(sea_new) <- paste(getNames(sea_new),"Sea",sep=".") - + getNames(sea_new) <- paste(getNames(sea_new), "Sea", sep = ".") + # correct 1-thru-data - data[,,"1-thru"] <- data[,,"1-thru"] * (1 - Sea/100) + data[, , "1-thru"] <- data[, , "1-thru"] * (1 - Sea / 100) # add sea data to data - data <- mbind(data,sea_new) - + data <- mbind(data, sea_new) + # check if all categories sum up to 100% - check <- new.magpie(getRegions(data),getYears(data),id) + check <- new.magpie(getRegions(data), getYears(data), id) for (i in id) { - check[,,i] <- dimSums(data[,,i],dim=3.2) + check[, , i] <- dimSums(data[, , i], dim = 3.2) } - if(!all(check==100)) { stop("sum of categorie XXX is not 100%")} - + if (!all(check == 100)) { + stop("sum of categorie XXX is not 100%") + } + # read in mapping to REMIND technologies - map_table <- read_excel(toolGetMapping(type = "sectoral", name = "TechnologyMappingDavies2REMIND.xlsx", - returnPathOnly = TRUE, where = "mappingfolder")) + map_table <- toolGetMapping( + type = "sectoral", + name = "techmappingDaviesToREMIND.csv", + where = "mrremind" + ) map <- list() - map$davies <- paste(map_table$'Davies Source/Technology',map_table$'Davies Cooling',sep=".") - map$remind <- paste(map_table$'REMIND Technology',map_table$'REMIND Cooling',sep=".") - + map$davies <- paste(map_table$Davies.Source.Technology, map_table$Davies.Cooling, sep = ".") + map$remind <- paste(map_table$REMIND.Technology, map_table$REMIND.Cooling, sep = ".") + + # calculate REMIND input in REMIND categories - output <- new.magpie(getRegions(data),getYears(data),map$remind) - output[,,] <- 0 - for(d in 1:length(map$davies)){ - if( !map$davies[d] == "-.-"){ - output[,,map$remind[d]] <- data[,,map$davies[d]] + output <- new.magpie(getRegions(data), getYears(data), map$remind) + output[, , ] <- 0 + for (d in 1:length(map$davies)) { + if (!map$davies[d] == "-.-") { + output[, , map$remind[d]] <- data[, , map$davies[d]] } } - + + # remove no longer used technologies pcc and pco + output <- output[, , c("pcc", "pco"), invert = TRUE] + # add assumed data - output[,,"geohdr.tower"] <- 70 - output[,,"geohdr.dry"] <- 20 - output[,,"geohdr.hybrid"] <- 10 - output[,,"hydro.default"] <- 100 - output[,,"wind.default"] <- 100 - output[,,"spv.default"] <- 100 - output[,,"csp.tower"] <- 70 - output[,,"csp.dry"] <- 20 - output[,,"csp.hybrid"] <- 10 - - outputFuture <- new.magpie(getRegions(output),c(2020),getNames(output)) - outputFuture[,,] <- output[,,] - - #assign aggregation weight - weight <- dimSums(calcOutput("IO",subtype="output",aggregate=FALSE)[,2010,c("feelb","feeli")],dim=3) - - #set weights to zero for countries that were not contained in the GCAM2ISO mapping - weight["ALA",,] <- 0 - weight["ATA",,] <- 0 - weight["BES",,] <- 0 - weight["BLM",,] <- 0 - weight["CUW",,] <- 0 - weight["GGY",,] <- 0 - weight["IMN",,] <- 0 - weight["JEY",,] <- 0 - weight["MAF",,] <- 0 - weight["PSE",,] <- 0 - weight["SSD",,] <- 0 - weight["SXM",,] <- 0 - - return(list(x=outputFuture,weight=weight, - unit="% of cooling type technologies", - description="Cooling shares for different cooling technologies based on Davies et al. (2013) publication and using electricity use weights (aggregated based on IEA World Energy Balances, 2014) for regional mapping" + output[, , "geohdr.tower"] <- 70 + output[, , "geohdr.dry"] <- 20 + output[, , "geohdr.hybrid"] <- 10 + output[, , "hydro.default"] <- 100 + output[, , "wind.default"] <- 100 + output[, , "spv.default"] <- 100 + output[, , "csp.tower"] <- 70 + output[, , "csp.dry"] <- 20 + output[, , "csp.hybrid"] <- 10 + + outputFuture <- new.magpie(getRegions(output), c(2020), getNames(output)) + outputFuture[, , ] <- output[, , ] + + # assign aggregation weight + weight <- dimSums(calcOutput("IO", subtype = "output", aggregate = FALSE)[, 2010, c("feelb", "feeli")], dim = 3) + + # set weights to zero for countries that were not contained in the GCAM2ISO mapping + weight["ALA", , ] <- 0 + weight["ATA", , ] <- 0 + weight["BES", , ] <- 0 + weight["BLM", , ] <- 0 + weight["CUW", , ] <- 0 + weight["GGY", , ] <- 0 + weight["IMN", , ] <- 0 + weight["JEY", , ] <- 0 + weight["MAF", , ] <- 0 + weight["PSE", , ] <- 0 + weight["SSD", , ] <- 0 + weight["SXM", , ] <- 0 + + return(list( + x = outputFuture, + weight = weight, + unit = "% of cooling type technologies", + description = c( + "Cooling shares for different cooling technologies based on ", + "Davies et al. (2013) publication and using electricity use weights ", + "(aggregated based on IEA World Energy Balances, 2014) for regional mapping" + ) )) } diff --git a/R/calcWaterConsCoef.R b/R/calcWaterConsCoef.R index 21397a3b..3c66b614 100644 --- a/R/calcWaterConsCoef.R +++ b/R/calcWaterConsCoef.R @@ -29,9 +29,10 @@ calcWaterConsCoef <- function() { # read in mapping to REMIND technologies map_table <- toolGetMapping( type = "sectoral", - name = "mappingMacknicktoREMIND.csv", + name = "techmappingMacknickToREMIND.csv", where = "mrremind" ) + map <- list() map$macknick <- paste(map_table$Macknick.Source, map_table$Macknick.Technology, map_table$Macknick.Cooling, diff --git a/inst/extdata/sectoral/techmappingDaviesToREMIND.csv b/inst/extdata/sectoral/techmappingDaviesToREMIND.csv new file mode 100644 index 00000000..876e476c --- /dev/null +++ b/inst/extdata/sectoral/techmappingDaviesToREMIND.csv @@ -0,0 +1,70 @@ +"REMIND Source";"REMIND Technology";"REMIND Cooling";"Davies Source/Technology";"Davies Cooling" +"pegas";"ngcc";"tower";"Combined Cycle";"WT" +"pegas";"ngcc";"once";"Combined Cycle";"1-thru" +"pegas";"ngcc";"pond";"Combined Cycle";"Pond" +"pegas";"ngcc";"dry";"Combined Cycle";"Dry" +"pegas";"ngccc";"tower";"Combined Cycle";"WT" +"pegas";"ngccc";"once";"Combined Cycle";"1-thru" +"pegas";"ngccc";"pond";"Combined Cycle";"Pond" +"pegas";"ngccc";"dry";"Combined Cycle";"Dry" +"pegas";"ngt";"tower";"Other fossil/bio";"WT" +"pegas";"ngt";"once";"Other fossil/bio";"1-thru" +"pegas";"ngt";"pond";"Other fossil/bio";"Pond" +"pegas";"ngt";"dry";"Other fossil/bio";"Dry" +"pegas";"gaschp";"tower";"Other fossil/bio";"WT" +"pegas";"gaschp";"once";"Other fossil/bio";"1-thru" +"pegas";"gaschp";"pond";"Other fossil/bio";"Pond" +"pegas";"gaschp";"dry";"Other fossil/bio";"Dry" +"pecoal";"igcc";"tower";"Combined Cycle";"WT" +"pecoal";"igcc";"once";"Combined Cycle";"1-thru" +"pecoal";"igcc";"pond";"Combined Cycle";"Pond" +"pecoal";"igcc";"dry";"Combined Cycle";"Dry" +"pecoal";"igccc";"tower";"Combined Cycle";"WT" +"pecoal";"igccc";"once";"Combined Cycle";"1-thru" +"pecoal";"igccc";"pond";"Combined Cycle";"Pond" +"pecoal";"igccc";"dry";"Combined Cycle";"Dry" +"pecoal";"pc";"tower";"Coal";"WT" +"pecoal";"pc";"once";"Coal";"1-thru" +"pecoal";"pc";"pond";"Coal";"Pond" +"pecoal";"pc";"dry";"Coal";"Dry" +"pecoal";"pcc";"tower";"Coal";"WT" +"pecoal";"pcc";"once";"Coal";"1-thru" +"pecoal";"pcc";"pond";"Coal";"Pond" +"pecoal";"pcc";"dry";"Coal";"Dry" +"pecoal";"pco";"tower";"Coal";"WT" +"pecoal";"pco";"once";"Coal";"1-thru" +"pecoal";"pco";"pond";"Coal";"Pond" +"pecoal";"pco";"dry";"Coal";"Dry" +"pecoal";"coalchp";"tower";"Coal";"WT" +"pecoal";"coalchp";"once";"Coal";"1-thru" +"pecoal";"coalchp";"pond";"Coal";"Pond" +"pecoal";"coalchp";"dry";"Coal";"Dry" +"peoil";"dot";"tower";"Other fossil/bio";"WT" +"peoil";"dot";"once";"Other fossil/bio";"1-thru" +"peoil";"dot";"pond";"Other fossil/bio";"Pond" +"peoil";"dot";"dry";"Other fossil/bio";"Dry" +"peur";"tnrs";"tower";"Nuclear";"WT" +"peur";"tnrs";"once";"Nuclear";"1-thru" +"peur";"tnrs";"pond";"Nuclear";"Pond" +"peur";"tnrs";"dry";"Nuclear";"Dry" +"pebiolc";"biochp";"tower";"Other fossil/bio";"WT" +"pebiolc";"biochp";"once";"Other fossil/bio";"1-thru" +"pebiolc";"biochp";"pond";"Other fossil/bio";"Pond" +"pebiolc";"biochp";"dry";"Other fossil/bio";"Dry" +"pebiolc";"bioigcc";"tower";"Combined Cycle";"WT" +"pebiolc";"bioigcc";"once";"Combined Cycle";"1-thru" +"pebiolc";"bioigcc";"pond";"Combined Cycle";"Pond" +"pebiolc";"bioigcc";"dry";"Combined Cycle";"Dry" +"pebiolc";"bioigccc";"tower";"Combined Cycle";"WT" +"pebiolc";"bioigccc";"once";"Combined Cycle";"1-thru" +"pebiolc";"bioigccc";"pond";"Combined Cycle";"Pond" +"pebiolc";"bioigccc";"dry";"Combined Cycle";"Dry" +"pegeo";"geohdr";"tower";"-";"-" +"pegeo";"geohdr";"dry";"-";"-" +"pegeo";"geohdr";"hybrid";"-";"-" +"pehyd";"hydro";"default";"-";"-" +"pewin";"wind";"default";"-";"-" +"pesol";"spv";"default";"-";"-" +"pesol";"csp";"tower";"-";"-" +"pesol";"csp";"dry";"-";"-" +"pesol";"csp";"hybrid";"-";"-" diff --git a/inst/extdata/sectoral/mappingMacknicktoREMIND.csv b/inst/extdata/sectoral/techmappingMacknickToREMIND.csv similarity index 100% rename from inst/extdata/sectoral/mappingMacknicktoREMIND.csv rename to inst/extdata/sectoral/techmappingMacknickToREMIND.csv