Added one set of cost data

Analysis.r

@@ -3,6 +3,7 @@ library(RcppRoll)
 RES <- readRDS("Results/Storage_Values_by_Facility_and_Variable_Discounts.Rds")
 RES[[1]]
 names(RES)
+RES$Per_10.5
 read_csv("Data/Curie_Spent_Fuel_Site_Totals.csv")
 CDATA <- RES$Per_5  %>% left_join(read_csv("Data/Curie_Spent_Fuel_Site_Totals.csv")) %>%  mutate(Revenue=parse_number(Revenue),Year=parse_number(Year),Marginal_Value=Revenue/Total_Tons) %>% select(Facility,Year,Revenue,Marginal_Value,Total_Tons)
 CDATA <- CDATA %>% group_by(Year) %>% arrange(Year,desc(Marginal_Value)) %>% mutate(CIFS_total=cumsum(Total_Tons)) %>% ungroup 

Cost_Data_Proc.r

@@ -0,0 +1,52 @@
+library(tidyverse)
+library(fixest)
+ISFSI <- read_csv("./Data/Raw_Data/Cost_Tables/Table_C-9_Number_of_ISFSIs_by_Project_Plan.csv")
+ONE <- ISFSI[1:3] 
+colnames(ONE) <- c("Year","Active","Decom")
+ONE <- ONE %>% mutate(Phase="Partial",Cost_Assumption="Low")
+
+TWO <- ISFSI[,c(1,4:5)] 
+colnames(TWO) <- c("Year","Active","Decom")
+TWO <- TWO%>% mutate(Phase="Full",Cost_Assumption="Low")
+
+THREE <- ISFSI[,c(1,6:7)] 
+colnames(THREE) <- c("Year","Active","Decom")
+THREE <- THREE %>% mutate(Phase="Partial",Cost_Assumption="High")
+
+FOUR <- ISFSI[,c(1,8:9)] 
+colnames(FOUR) <- c("Year","Active","Decom")
+FOUR <- FOUR %>% mutate(Phase="Full",Cost_Assumption="High")
+ISFSI_NUM <- rbind(ONE,TWO,THREE,FOUR)
+SAVE_DIR <- "./Data/Cleaned_Data/"
+dir.create(SAVE_DIR,showWarnings=FALSE,recursive=TRUE)
+saveRDS(ISFSI_NUM,paste0(SAVE_DIR,"ISFSI_Data.Rds"))
+rm(ONE,TWO,THREE,FOUR)
+######CIFS costs
+CIFS <- rbind( read_csv("./Data/Raw_Data/Cost_Tables/Table_C-3_Undiscounted_Cost_Estimates_Phase_1_Low.csv") %>% mutate(Phase='Partial',Cost_Assumption="Low"),read_csv("./Data/Raw_Data/Cost_Tables/Table_C-4_Undiscounted_Cost_Estimates_Phase_1_High.csv") %>% mutate(Phase='Partial',Cost_Assumption="High"), read_csv("./Data/Raw_Data/Cost_Tables/Table_C-5_Undiscounted_Cost_Estimates_Full_Low.csv") %>% mutate(Phase='Full',Cost_Assumption="Low"), read_csv("./Data/Raw_Data/Cost_Tables/Table_C-6_Undiscounted_Cost_Estimates_Full_High.csv") %>% mutate(Phase='Full',Cost_Assumption="High"))
+
+######Onsite costs
+ONSITE <- rbind( read_csv("./Data/Raw_Data/Cost_Tables/Table_C-10_Undiscounted_No_Action_Phase_1_Low.csv") %>% mutate(Phase='Partial',Cost_Assumption="Low"),read_csv("./Data/Raw_Data/Cost_Tables/Table_C-11_Undiscounted_No_Action_Phase_1_High.csv") %>% mutate(Phase='Partial',Cost_Assumption="High"), read_csv("./Data/Raw_Data/Cost_Tables/Table_C-12_Undiscounted_No_Action_Full_Low.csv") %>% mutate(Phase='Full',Cost_Assumption="Low"), read_csv("./Data/Raw_Data/Cost_Tables/Table_C-13_Undiscounted_No_Action_Full_High.csv") %>% mutate(Phase='Full',Cost_Assumption="High"))
+ISFSI_NUM %>% filter(Year>=30,Phase=='Full') %>% print(n=100)
+#######
+SUMMARY <- ONSITE %>% inner_join(ISFSI_NUM) %>% group_by(Year,Cost_Assumption) %>% summarize(Decom_num=Decom,OP=Operations_Active/ifelse(Active==0,1,Active),Decom=Operations_Decom/ifelse(Decom==0,1,Decom))
+OP <- SUMMARY %>% filter(OP!=0) %>% pull(OP) %>% mean
+TEST <-SUMMARY %>% filter(Cost_Assumption=='High')  %>% unique
+hist(TEST$Decom)
+
+TEST <-SUMMARY   %>% unique
+hist(TEST$Decom)
+TEST %>% filter(OP!=0,Year>28) %>% print(n=100)
+SUMMARY <- SUMMARY %>% mutate(CLOSING=ifelse(Year>=31,1,0))
+SUMMARY
+(10*77964491)/36
+(2*125682289)/9
+TEST
+77964491/108647430
+feols(Decom~Decom_num+CLOSING*Year,SUMMARY %>% filter(OP!=0))
+hist(SUMMARY$Decom)
+#####
+M <- (779644907-251364578)/(40000-5000)
+C <- 779644907-M*40000
+(M*150000+C)/10^6
+
+

Data/Raw_Data/Cost_Tables/Table_C-10_Undiscounted_No_Action_Phase_1_Low.csv

@@ -0,0 +1,43 @@
+
+Year,Operations_Active,Operations_Decom,SNF_Transportation,Total
+1,1086474,86917944,0,88004418
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+

Data/Raw_Data/Cost_Tables/Table_C-11_Undiscounted_No_Action_Phase_1_High.csv

@@ -0,0 +1,43 @@
+
+Year,Operations_Active,Operations_Decom,SNF_Transportation,Total
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+

Data/Raw_Data/Cost_Tables/Table_C-12_Undiscounted_No_Action_Full_Low.csv

@@ -0,0 +1,42 @@
+
+Year,Operations_Active,Operations_Decom,SNF_Transportation,Total
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Data/Raw_Data/Cost_Tables/Table_C-13_Undiscounted_No_Action_Full_High.csv

@@ -0,0 +1,41 @@
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Data/Raw_Data/Cost_Tables/Table_C-3_Undiscounted_Cost_Estimates_Phase_1_Low.csv

@@ -0,0 +1,42 @@
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Data/Raw_Data/Cost_Tables/Table_C-4_Undiscounted_Cost_Estimates_Phase_1_High.csv

@@ -0,0 +1,42 @@
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Data/Raw_Data/Cost_Tables/Table_C-5_Undiscounted_Cost_Estimates_Full_Low.csv

@@ -0,0 +1,44 @@
+
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Data/Raw_Data/Cost_Tables/Table_C-6_Undiscounted_Cost_Estimates_Full_High.csv

@@ -0,0 +1,43 @@
+
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+9,0,0,12404499,0,0,12404499
+10,49658192,9340707,12290023,0,0,71288921
+11,93893836,16983102,12621753,0,0,123498692
+12,58686954,11039017,12779680,0,0,82505650
+13,49658192,9340707,12757955,0,0,71756854
+14,49658192,9340707,12523989,0,0,71522888
+15,0,0,12404499,0,0,12404499
+16,0,0,12170532,0,0,12170532
+17,49658192,9340707,12290023,0,0,71288921
+18,90287622,16983102,12621753,0,0,119892477
+19,9028762,1698310,12660190,0,0,23387262
+20,49658192,9340707,12523989,0,0,71522888
+21,108142352,16983102,12621753,0,0,137747207
+22,90287622,16983102,12855719,0,0,120126442
+23,67715717,12737327,13035372,0,0,93488416
+24,90287622,16983102,12855719,0,0,120126442
+25,90287622,16983102,12855719,0,0,120126442
+26,90287622,16983102,13089686,0,0,120360409
+27,90287622,16983102,13089686,0,0,120360409
+28,90287622,16983102,13089686,0,0,120360409
+29,90287622,16983102,13089686,0,0,120360409
+30,54172573,10189862,12768818,0,0,77131252
+31,3606215,0,12638465,77964491,0,94209170
+32,0,0,12170532,77964491,0,90135023
+33,0,0,12170532,77964491,0,90135023
+34,0,0,12170532,77964491,0,90135023
+35,0,0,12170532,77964491,0,90135023
+36,0,0,12170532,77964491,0,90135023
+37,0,0,12170532,77964491,0,90135023
+38,0,0,12170532,77964491,0,90135023
+39,0,0,12170532,77964491,0,90135023
+40,0,0,12170532,77964491,0,90135023
+41,0,0,12170532,0,405340890,417511423

Data/Raw_Data/Cost_Tables/Table_C-9_Number_of_ISFSIs_by_Project_Plan.csv

@@ -0,0 +1,43 @@
+
+Year,S1_Phase1_Active,S1_Phase1_Decom,S1_Full_Active,S1_Full_Decom,S2_Phase1_Active,S2_Phase1_Decom,S2_Full_Active,S2_Full_Decom
+1,1,8,28,8,1,8,28,8
+2,1,8,28,8,0,9,27,9
+3,0,9,27,9,0,9,27,9
+4,0,9,27,9,0,9,26,10
+5,0,9,26,10,0,9,26,10
+6,0,9,26,10,0,9,24,12
+7,0,9,26,10,0,9,23,13
+8,0,9,26,10,0,9,22,14
+9,0,9,26,10,0,9,21,15
+10,0,9,26,10,0,9,21,15
+11,0,9,26,10,0,9,21,15
+12,0,9,26,10,0,9,20,16
+13,0,9,26,10,0,9,18,18
+14,0,9,26,10,0,9,18,18
+15,0,9,26,10,0,9,17,19
+16,0,9,26,10,0,9,15,21
+17,0,9,26,10,0,9,13,23
+18,0,9,26,10,0,9,12,24
+19,0,9,26,10,0,9,10,26
+20,0,9,26,10,0,9,6,30
+21,0,9,26,10,0,9,5,35
+22,0,9,26,10,0,9,5,35
+23,0,9,26,10,0,9,0,36
+24,0,9,26,10,0,9,0,36
+25,0,9,26,10,0,9,0,36
+26,0,9,26,10,0,9,0,36
+27,0,9,26,10,0,9,0,36
+28,0,9,26,10,0,9,0,36
+29,0,9,26,10,0,9,0,36
+30,0,9,26,10,0,9,0,36
+31,0,9,26,10,0,9,0,36
+32,0,9,26,10,0,9,0,36
+33,0,9,26,10,0,9,0,36
+34,0,9,26,10,0,9,0,36
+35,0,9,26,10,0,9,0,36
+36,0,9,26,10,0,9,0,36
+37,0,9,26,10,0,9,0,36
+38,0,9,26,10,0,9,0,36
+39,0,9,26,10,0,9,0,36
+40,0,9,26,10,0,9,0,36
+

Data/Raw_Data/Cost_Tables/test.r

@@ -0,0 +1,52 @@
+library(tidyverse)
+#########CIFS Costs
+DAT <- read_csv("Table_C-3_Undiscounted_Cost_Estimates_Phase_1.csv")
+rowSums(DAT[,2:6])-DAT$Total
+
+DAT <- read_csv("Table_C-4_Undiscounted_Cost_Estimates_Phase_1_High.csv")
+rowSums(DAT[,2:6])-DAT$Total
+sum(DAT[,2:6])
+sum(DAT[,7])
+DAT[5,7]-sum(DAT[5,2:6])
+61242023-(40629430+7642396+12970196)
+
+DAT <- read_csv("Table_C-5_Undiscounted_Cost_Estimates_Full_Low.csv")
+rowSums(DAT[,2:6])-DAT$Total
+
+DAT <- read_csv("Table_C-6_Undiscounted_Cost_Estimates_Full_High.csv")
+rowSums(DAT[,2:6])-DAT$Total
+sum(DAT[,2:6])
+
+################ISFS
+DAT <- read_csv("Table_C-9_Number_of_ISFSIs_by_Project_Plan.csv")
+ONE <- DAT[1:3] 
+colnames(ONE) <- c("Year","Active","Decom")
+ONE <- ONE %>% mutate(Phase="Partial",Cost_Assumption="Low")
+
+TWO <- DAT[,c(1,4:5)] 
+colnames(TWO) <- c("Year","Active","Decom")
+TWO <- TWO%>% mutate(Phase="Full",Cost_Assumption="Low")
+
+THREE <- DAT[,c(1,6:7)] 
+colnames(THREE) <- c("Year","Active","Decom")
+THREE <- THREE %>% mutate(Phase="Partial",Cost_Assumption="High")
+
+FOUR <- DAT[,c(1,8:9)] 
+colnames(FOUR) <- c("Year","Active","Decom")
+FOUR <- FOUR %>% mutate(Phase="Full",Cost_Assumption="High")
+ISFSI_NUM <- rbind(ONE,TWO,THREE,FOUR)
+ISFSI_NUM  %>% filter(Year==40)
+
+####No Action Costs
+DAT <- read_csv("Table_C-10_Undiscounted_No_Action_Phase_1_Low.csv")
+rowSums(DAT[,2:4])-DAT$Total
+sum(DAT$Total)
+#Table 11 is identical to Table 10 so not check needed
+DAT <- read_csv("Table_C-12_Undiscounted_No_Action_Full_Low.csv")
+rowSums(DAT[,2:4])-DAT$Total
+sum(DAT$Total)
+
+DAT <- read_csv("Table_C-13_Undiscounted_No_Action_Full_High.csv")
+rowSums(DAT[,2:4])-DAT$Total
+sum(DAT$Total)
+

Data_Proc.r

@@ -1,8 +1,8 @@
 library(tidyverse)
 library(parallel)
 
-TS <- read_csv("Data/Curie_Spent_Fuel_Timeline.csv")
+TS <- read_csv("Data/Raw_Data//Curie_Spent_Fuel_Timeline.csv")
-TOTAL <- read_csv("Data/Curie_Spent_Fuel_Site_Totals.csv") %>% mutate(OP_YEAR=year(Op_Date_Min),CLOSE_YEAR=year(Close_Date_Max))%>% select(Facility,Total_Assemblies,Total_Tons,OP_YEAR,CLOSE_YEAR) 
+TOTAL <- read_csv("Data/Raw_Data/Curie_Spent_Fuel_Site_Totals.csv") %>% mutate(OP_YEAR=year(Op_Date_Min),CLOSE_YEAR=year(Close_Date_Max))%>% select(Facility,Total_Assemblies,Total_Tons,OP_YEAR,CLOSE_YEAR) 
 ###########Series of functions to calculate the gross consumer surplus from a CIFS for each facility, in each year from 1960 to 2082.
 
 #Function to find the net present revenue of a facility,given a discount rate, and the current year, and year the facility will close. This is the sum of discounted costs that WOULD have taken place if the facility was not built 
@@ -18,7 +18,7 @@ NPV_CALC <- function(r,DATA=TOTAL,YEARS=1960:2083){
 	Facility <- pull(DATA,Facility)
 	RES <- cbind(Facility,do.call(cbind,lapply(YEARS,function(x){VALUE_ADD_SINGLE_YEAR(r,x,DATA$CLOSE_YEAR)})))
 colnames(RES) <- c("Facility",YEARS) 
-	RES <- as_tibble(RES) %>% pivot_longer(cols=-Facility,names_to="Year",values_to="Revenue") %>% arrange(Year)
+	RES <- as_tibble(RES) %>% pivot_longer(cols=-Facility,names_to="Year",values_to="Revenue") %>% arrange(Year) %>% mutate(Year=parse_number(Year),Revenue=parse_number(Revenue))
 	return(RES)
 }
 #A function which returns a list, of net present revenue calculation tables (facility by year) for a range of possible discount rates. This allows for the results to be quickly looked up, when we want to adjust the time value of money. These results will need to be combined with costs to calculate NPV