R/readIEA_WEO.R

In pik-piam/moinput: Model Operations Input Data Library

#' Read IEA World Energy Outlook data
#' 
#' @description Read-in IEA WEO 2016 data for investment costs, O&M costs and Efficiency of different technologies, and 
#' WEO 2017 data for historical electricity capacities (GW), generation (TWh) or emissions (Mt CO2).
#' 
#' @param subtype data subtype. Either "Capacity", "Generation", "Emissions", "Investment Costs", "O&M Costs" or "Efficiency"
#' @return magpie object of the WEO data on generation (TWh), capacities (GW), emissions (Mt CO2) or disaggregated investment cost as magpie object  
#' @author Renato Rodrigues and Aman Malik
#' @seealso \code{\link{readSource}}
#' @examples
#' 
#' \dontrun{ a <- readSource(type="WEO",subtype="Capacity")
#' }
#'   
#' @importFrom tidyr gather
#' @importFrom readxl read_excel

readIEA_WEO <- function(subtype){
  
    if ((subtype=="Invest_Costs") || (subtype=="O&M_Costs") || (subtype=="Efficiency")) {
      
      # read WEO 2016 input files- values are from the  New Policy  scenario, except for CCS costs which are from 450 scenario.
      #Coal
      input_coal <- read.csv(file = "WEO_2016-coal.csv",na.strings = "n.a.",stringsAsFactors = F)
      input_coal$maintech <- "Coal"
      # Gas
      input_gas <-  read.csv(file = "WEO_2016-gas.csv",na.strings = "n.a.",stringsAsFactors = F)
      input_gas$maintech <- "Gas"
      # Tech with CCS
      input_ccs <- read.csv(file = "WEO_2016-ccs.csv",na.strings = "n.a.",stringsAsFactors = F)
      input_ccs$maintech <- "CCS"
      # Tech with NUC
      input_nuc <- read.csv(file = "WEO_2016-nuclear.csv",na.strings = "n.a.",stringsAsFactors = F)
      input_nuc$maintech <- "Nuclear"
      # Tech with REN
      input_ren <-  read.csv(file = "WEO_2016-ren.csv",na.strings = "n.a.",stringsAsFactors = F)
      input_ren$maintech <- "Renewables"
      # Special case for hydro, values are taken not from the IEA database.
      input_hydro <- read.csv(file = "hydro.csv",stringsAsFactors = F)
      # removing 2025 values
      input_hydro <- input_hydro %>% select(-5)
      
      # 2040 values same as 2030 values
      input_hydro$X2040 <- input_hydro$X2030
      input_hydro <- cbind(input_hydro,input_ren[1:12,7:14])
      # input_hydro <- input_hydro[,c(1:5,15,6:14)]
      input_hydro[,7:14] <- 0
      input_hydro$maintech <- "Hydro_2"
      #col.names = c("tech","region","2015","2020","2030","2040","2015",  "2020","2030","2040","2015","2020","2030","2040")
      input_all <- bind_rows(input_coal,input_gas,input_ccs,input_nuc,input_ren,input_hydro)
     
      if (subtype=="Invest_Costs"){
        input <- input_all[,c(15,1:6)]
        colnames(input)[4:7] <- c(2015,2020,2030,2040)
        input <- input%>% 
          gather(4:7,key = "Year",value="costs")
        
        x <- as.magpie(input,spatial=3,temporal=4,datacol=5)
      } else if (subtype=="O&M_Costs"){
        input <- input_all[,c(15,1:2,7:10)]
        colnames(input)[4:7] <- c(2015,2020,2030,2040)
        input <- input %>% 
          gather(4:7,key = "Year",value="costs")
   
        x <- as.magpie(input,spatial=3,temporal=4,datacol=5)
      } else if (subtype=="Efficiency"){
        input <- input_all[,c(15,1:2,11:14)]
        colnames(input)[4:7] <- c(2015,2020,2030,2040)
        input <- input %>% 
          gather(4:7,key = "Year",value="efficiency")
        x <- as.magpie(input,spatial=3,temporal=4,datacol=5)
      }
      
    } else if ((subtype=="Capacity") || (subtype=="Generation") || (subtype=="Emissions")) {
      
      if (subtype == "Capacity") {
          data <- read.csv("WEO_2017/WEO-capacity.csv",sep=";")[,c(2,3,4,5)]
      } else if (subtype== "Generation") {
          data <- read.csv("WEO_2017/WEO-generation.csv",sep=";")[,c(2,3,4,5)]
      } else if (subtype== "Emissions") {
          data <- read.csv("WEO_2017/WEO-EmiCO2.csv",sep=";")[,c(2,3,4,5)]
          # data <- read.csv("WEO_2017/WEO-Emi_seel_CO2.csv",sep=";")[,c(2,3,4,5)]
          # data <- read.csv("WEO_2017/WEO-Emi_fe_CO2.csv",sep=";")[,c(2,3,4,5)]
      }  
      # creating capacity, generation or emissions magpie object
      x <- as.magpie(data,temporal=2,spatial=1,datacol=4)
        
    } else {
        stop("Not a valid subtype!")
    }
    # x[,,] <- as.numeric(x[,,])
    return(x)
  }