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Add some missing values. Looks complete now

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Alex Gebben Work 2026-03-12 13:37:57 -06:00
parent 5f17aa5acf
commit 544c99e811
1 changed files with 11 additions and 2 deletions
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13
REMI_Inputs.r
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@ -23,6 +23,7 @@ CAPITAL_SCHEDULE_EST <- c(250,500,250,500,0)/2 + c(0,250,500,250,500)/2
CAPITAL_SCHEDULE_EST<- CAPITAL_SCHEDULE_EST/sum(SCHEDULE) CAPITAL_SCHEDULE_EST<- CAPITAL_SCHEDULE_EST/sum(SCHEDULE)
BUILDING <- BUILDING*CAPITAL_SCHEDULE_EST #Output of construction industry BUILDING <- BUILDING*CAPITAL_SCHEDULE_EST #Output of construction industry
COMPUTERS <- COMPUTERS*CAPITAL_SCHEDULE_EST #Purchases of Computers COMPUTERS <- COMPUTERS*CAPITAL_SCHEDULE_EST #Purchases of Computers
sum(COMPUTERS )
OTHER <- OTHER*CAPITAL_SCHEDULE_EST #Other purchases OTHER <- OTHER*CAPITAL_SCHEDULE_EST #Other purchases
DOLLAR_VALUES <- cbind(2029:2033,BUILDING,COMPUTERS,OTHER) %>% as_tibble DOLLAR_VALUES <- cbind(2029:2033,BUILDING,COMPUTERS,OTHER) %>% as_tibble
colnames(DOLLAR_VALUES )[1] <- "Year" colnames(DOLLAR_VALUES )[1] <- "Year"
@ -47,6 +48,7 @@ DOLLARS_PER_MW <- DOLLARS_PER_KW*1000
MILL_DOLLARS_PER_MW <- DOLLARS_PER_MW/10^6 MILL_DOLLARS_PER_MW <- DOLLARS_PER_MW/10^6
CCG_CONSTRUCTION_COSTS <- CCG_SCHEDULE*MILL_DOLLARS_PER_MW CCG_CONSTRUCTION_COSTS <- CCG_SCHEDULE*MILL_DOLLARS_PER_MW
#DOLLAR_VALUES$CCG_COST <- CCG_CONSTRUCTION_COSTS
CCG_CAPITAL_COST <- CCG_COST-CCG_CONSTRUCTION_COSTS[5] #Remove the construction cost to estimate final capital costs CCG_CAPITAL_COST <- CCG_COST-CCG_CONSTRUCTION_COSTS[5] #Remove the construction cost to estimate final capital costs
CCG <- CCG_CAPITAL_COST *(CCG_SCHEDULE/sum(CCG_SCHEDULE)) CCG <- CCG_CAPITAL_COST *(CCG_SCHEDULE/sum(CCG_SCHEDULE))
TURBINE <- CCG +RECIP TURBINE <- CCG +RECIP
@ -123,7 +125,14 @@ CONST_EMPLOYMENT_PRED
CONST_EMPLOYMENT_PRED[1] <- CONST_EMPLOYMENT_PRED[1]-EMP_2029 CONST_EMPLOYMENT_PRED[1] <- CONST_EMPLOYMENT_PRED[1]-EMP_2029
CONST_EMPLOYMENT_PRED <- c(EMP_2029,CONST_EMPLOYMENT_PRED) CONST_EMPLOYMENT_PRED <- c(EMP_2029,CONST_EMPLOYMENT_PRED)
CONST_EMPLOYMENT_PRED <- CONST_EMPLOYMENT_PRED[c(1:3,5,4)] #Assume the CCG is built mostly in the previous year, but single cycles are same year, based on Enyo data sheet CONST_EMPLOYMENT_PRED <- CONST_EMPLOYMENT_PRED[c(1:3,5,4)] #Assume the CCG is built mostly in the previous year, but single cycles are same year, based on Enyo data sheet
ALL_VALUES$TURBINE_CONST_WORKERS <- CONST_EMPLOYMENT_PRED ALL_VALUES$TURBINE_CONST_WORKERS <- CONST_EMPLOYMENT_PRED
ALL_VALUES ###Data center values
OPERATIONAL_EMP_COEF <- (0.15+0.2)/2
DATA_CENTER_EMP <- round(OPERATIONAL_EMP_COEF* c(0,cumsum(SCHEDULE ))) ##MW of active data center capacity times emplotyment intesity coefcient
###see(https://hamminstitute.org/site-files/documents/data_center_workforce.pdf)0/see
ALL_VALUES$DATA_CENTER_EMP <- DATA_CENTER_EMP
ALL_VALUES
ALL_VALUES %>% select(-BUILDING,-COMPUTERS,-BESS,-DATA_CENTER_EMP,-POWER_OPERATORS,-TURBINE_CONST_WORKERS,-OTHER)