Difference between revisions of "Building model"

library(OpasnetUtils)

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

buildings <- Ovariable("buildings", 
	dependencies = data.frame(Name = c(
		"stockBuildings",
		"heatingShares",
		"efficiencyShares",
		"changeBuildings",
		"renovationShares", 
		"renovationRate", 
		"obstime" 
	)),
	formula = function(...) {

		#### Calculate cb ie. those buildings that were built between Time-1 and Time.
		#### This has two parts: the stock (stockBuildings) is treated as net construction rate
		#### by assuming that after construction Time nothing is demolished.
		#### Then this is added to the direct construction data (changeBuildings).

#		### This code can be used to change cumulative building stock data to construction rates of periods.
#		stockBuildings@output$Time <- as.numeric(as.character(stockBuildings@output$Time))
#		years <- sort(unique(stockBuildings@output$Time))
#		cb <- stockBuildings
#		cb@output$Time <- years[match(cb@output$Time, years) + 1] # Frame shift with time, years 2:n.
#		cb@output <- subset(cb@output, !is.na(Time))
#		cb <- stockBuildings - cb
#		cb@output <- orbind(cb, subset(stockBuildings@output, Time = years[1])) # First year
		
		######## This function applies renovations to the building stock and then follows it in time.

		renovate <- function(
			renoStock, # building stock to be renovated
			renovationShares, # shares of different renovations (see Answer)
			renovationRate, # renovation rate (see Answer)
			obstime # observation times (see Answer)
		) {
			reno <- renoStock * renovationShares
			marginals <- colnames(reno@output)[reno@marginal]
			reno@output$Age <- as.numeric(as.character(reno@output$Startyear)) - # Startyear is the time of renovation
				as.numeric(as.character(reno@output$Time)) # Time is the time of construction
			reno@marginal <- colnames(reno@output) %in% marginals

			reno <- reno * renovationRate # continuousOps(reno, renovationRate, '*') FIX continuousOps before using
			reno <- oapply(reno, cols = c("Age", "Time"), FUN = sum)

			out <- reno * -1 # Equal amount stops being non-renovated.
			out@output$Renovation <- "None"
			out <- orbind2(out, reno, use_fillna = TRUE) # Renovated buildings
			colnames(renoStock@output)[colnames(renoStock@output) == "Time"] <- "Startyear"
			out <- orbind2(
				out, 
				renoStock * Ovariable( # Add non-renovated buildings
					output = data.frame(Renovation = "None", Result = 1), 
					marginal = c(TRUE, FALSE),
				use_fillna = TRUE
				)
			)
	
			######## NA in indices will ruin timepoints. Therefore must do fillna but with warning.

			b <- character()
			for(i in colnames(out@output)[out@marginal]) {if(any(is.na(out@output[[i]]))) b <- c(b, i)}
			if(length(b) > 0) {
				out@output <- fillna(out@output, b)
				warning("Missing values had to be filled for timepoints by function fillna in indices: ", b, "\n")
			}

			out <- timepoints(out, obstime) # Accumulate over observation time.

			return(out)
		}

		########### Renovations of existing buildings. Heating and efficiency are applied afterwards,
		# so that they may change in the existing stock.

		stock <- renovate(stockBuildings, renovationShares, renovationRate, obstime)

		stock <- stock * heatingShares * efficiencyShares

		########### Renovations of constructed buildings. These must contain the heating and efficiency
		# data, and those cannot be changed afterwards.

		change <- renovate(changeBuildings, renovationShares, renovationRate, obstime)
		
		# Add buildings from stock and buildings from construction data

		out <- orbind2(
			stock, 
			change, 
			use_fillna = TRUE, 
			warn = "This should NOT happen: stock and change don't match when evaluating buildings"
		)
		out@output$Time <- as.numeric(as.character(out@output$Time))

		return(out)
	}
)

### HeatingEnergy

heatingEnergy <- Ovariable("heatingEnergy", 
	dependencies = data.frame(Name = c(
		"energyUse",
		"efficiencyRatio",
		"renovationRatio",
		"buildings"
	)),
	formula = function(...) {
		
		out <- buildings * energyUse * efficiencyRatio * renovationRatio
		out <- unkeep(out, prevresults = TRUE, sources = TRUE)
		out <- oapply(out, cols = c("Building"), FUN = sum)
		
		return(out)
	}
)

####### Calculate emissions

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

		out <- oapply(heatingEnergy, cols = c("Building", "Efficiency"), FUN = sum)
		out <- out * fuelShares * 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("Burner", "Fuel", "City_area"),
			FUN = sum
		)
		return(out)
	}
)

exposure <- Ovariable("exposure", 
	dependencies = data.frame(Name = c(
		"emissions", #  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
		"population"
	)),
	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 <- (emissions * out) * iF / BR / population # the actual equation
		out <- unkeep(out, prevresults = TRUE, sources = TRUE)
		out@output <- out@output[!out@output$Pollutant %in% c("CO2", "CO2official") , ]
		colnames(out@output)[colnames(out@output) == "Pollutant"] <- "Exposure_agent"
		out <- oapply(out, cols = c("Renovation"), FUN = sum)

		return(out)
	}
)

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

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