Difference between revisions of "Building model"

library(OpasnetUtils)

#########3# Calculate all building events (constructions, demolitions, renovations)

buildings <- Ovariable("buildings", 
	dependencies = data.frame(Name = c(
		"stockBuildings", # Building stock given as an amount at given timepoints
		"heatingShares", # Heating types of current buildings
		"efficiencyShares", # Energy efficiency types of current buildings
		"changeBuildings", # Construction or demolition rate as floor-m2. Indices Efficiency and 
			# Heating should be included here, if used.
#		"buildingTypes", # A dummy variable to combine two different indices: Building and Building2
		"renovationShares", # Fraction of renovation type when renovation is done.
		"rateBuildings", # Percentage of renovations and other relative changes per year
#		"eventyear", # A dummy variable to combine time periods to numerical time axis.
		"year" # A data.frame of years for which observations are calculated. This requires timepoints function.
	)),
	formula = function(...) {
		# Current building stock
		stock <- stockBuildings * heatingShares * efficiencyShares

		if(!"Built" %in% colnames(stock@output)) { # Make a duplicate of Time because Built is needed later.
			marginals <- colnames(stock@output)[stock@marginal]
			stock@output$Built <- stock@output$Time
			stock@marginal <- colnames(stock@output) %in% c(marginals, "Built")
		}

		#### Changes in building stock due to construction etc.
		
#		change <- changeBuildings 
		change <- timepoints(changeBuildings, obsyear, sumtimecol = FALSE) # Cumulative changes at certain timepoints.
		stock@output$Time <- as.numeric(as.character(stock@output$Time))
		stock@output$Built <- as.numeric(as.character(stock@output$Built))

		stock@output <- orbind(stock, change)
		stock@output$Age <- stock@output$Time - stock@output$Built
		stock@marginal <- colnames(stock@output) %in% c(
			"Age", 
			colnames(stock@output)[stock@marginal], 
			colnames(changeBuildings@output)[changeBuildings@marginal]
		)
		stock <- unkeep(stock, prevresults = TRUE, sources = TRUE)
#		nonrenovated <- oapply(stock, cols = character(), FUN = sum) # Simplify row structure
#		if("Renovation" %in% colnames(nonrenovated@output)) {nonrenovated@output <- subset(
#			nonrenovated@output, 
#			Renovation == "None", 
#			colnames(nonrenovated@output) != "Renovation"
#		)}

		reno <- nonrenovated * renovationShares
		
		# Floor area of renovations in ten years. Combine with continuous index Age.
		reno <- continuousOps(stock, renovationRate, '*') * renovationShares * 10 
		reno@output$Built <- reno@output$Time # Renovation is the new event.
		reno <- unkeep(reno, cols = c("Age", "Time"), sources = TRUE, prevresults = TRUE)

		temp2 <- orbind(temp1 * 1, reno * -1) # Equal amount stops being non-renovated.
		temp2$Renovation <- "None"
		temp2 <- orbind(temp2, reno) # Temp2: Construction + renovation in data.frame
		temp2$Renovation <- as.factor(temp2$Renovation)

		temp3 <- Ovariable(output = temp2)) # Temp3: Like Temp2 but ovariable
		temp3 <- unkeep(temp3, sources = TRUE, prevresults = TRUE)
#		temp3@output <- fillna(temp3@output, marginals = colnames(temp3@output)[temp3@marginal]) # WHY THIS? CANNOT FILLNA AMOUNTS!
#		colnames(temp3@output)[colnames(temp3@output) == "City area"] <- "City.area"

		# temp4: Drop redundant time indices
		temp4 <- oapply(temp3, cols = c("Built", "Age"), FUN = "sum", na.rm = TRUE)
#		temp4@output <- temp4@output[!is.na(result(temp4)) , ]

		# Calculate cumulative events at timepoints defined by obsyear.
		out <- timepoints(temp4, obsyear = obsyear)
		return(out)
	}
)

### HeatingEnergy

heatingEnergy <- Ovariable("heatingEnergy", 
	dependencies = data.frame(Name = c(
		"energyUse", # Energy consumption per floor area
		"efficiencyRatio", # Relative energy consumption compared with the efficiency group Old.
		"renovationRatio", # Relative energy consumption compared with the Renovation
		"buildings",
		"buildingTypes"
	)),
	formula = function(...) {
		
		out <- buildings * buildingTypes * energyUse * efficiencyRatio * renovationRatio
		
		return(out)
	}
)

####### Calculate emissions

emissions <- Ovariable("emissions", 
	dependencies = data.frame(
		Name = c(
			"heatingEnergy",
			"fuelTypes", 
			"emissionFactors"
		)
	),
	formula = function(...) {

		out <- oapply(heatingEnergy, cols = c("Building", "Efficiency"), FUN = sum)
		out <- out * fuelTypes * emissionFactors * 3.6  * 1E-9 # convert from kWh /a to MJ /a and mg to ton

		out <- unkeep(out * emissionLocations, sources = TRUE, prevresults = TRUE)

		out@output$Emission_site <- as.factor(ifelse(
			out@output$Emission_site == "At site of consumption",
			as.character(out@output$City_area),
			as.character(out@output$Emission_site)
		))

		out <- oapply(
			out,
			cols = c("Heating", "Burner", "Fuel", "City_area"),
			FUN = sum
		)
	}
)
#"Emission_site", "Emission_height", 

exposure <- Ovariable("exposure", 
	# emis is in ton /a
	# iF = conc (g /m3) * pop (#) * BR (m3 /s) / emis (g /s) <=> conc = emis * iF / BR / pop # conc is the exposure concentration
	dependencies = data.frame(Name = c("emis2", "iF", "pop")),
	formula = function(...) {
		BR <- 20 # Nominal breathing rate (m^3 /d)
		BR <- BR / 24 / 3600 # m^3 /s
		out <- 1E+12 / 365 / 24 / 3600 # Emission scaling from ton /a to ug /s.
		out <- (emis2 * out) * iF / BR / pop # the actual equation
		out <- unkeep(out, prevresults = TRUE, sources = TRUE)
		return(out)
	}
)

objects.store(buildings, heatingEnergy, emissions, exposure)

cat("Saved ovariables buildings, heatingEnergy, emissions, exposure\n")