Difference between revisions of "Building stock in Helsinki"

library(OpasnetUtils)
library(ggplot2)

objects.latest("Op_en7115", code_name = "initiate")

stockBuildings <- EvalOutput(stockBuildings)

ggplot(stockBuildings@output, aes(x = Time, weight = stockBuildingsResult, fill = Heating)) + 
	geom_bar(binwidth = 5) + theme_gray(base_size = 24) + 
	labs(
		title = "Current building stock (floor area) by heating type \n and year of construction", 
		x = "Construction year",
		y = expression("Floor area ( "*m^2*" )"))

ggplot(stockBuildings@output, aes(x = Time, weight = stockBuildingsResult, fill = Building)) + 
	geom_bar(binwidth = 5) + theme_gray(base_size = 24) + 
	labs(
		title = "Current building stock (floor area) by building type \n and year of construction", 
		x = "Construction year",
		y = expression("Floor area ( "*m^2*" )"))

library(OpasnetUtils)

# [[Building stock in Helsinki]], building stock, locations by city area (in A Finnish coordinate system)
#stockBuildings <- Ovariable("stockBuildings", ddata = "Op_en7115.stock_details")
#colnames(stockBuildings@data)[colnames(stockBuildings@data) == "Built"] <- "Time"
#colnames(stockBuildings@data)[colnames(stockBuildings@data) == "Postal code"] <- "City_area"

# [[Building stock in Helsinki]]
dat <- opbase.data("Op_en7115.stock_details")[ , c(
#	"Rakennus ID",
	"Sijainti",
	"Valmistumisaika",
#	"Julkisivumateriaali",
	"Käyttötarkoitus",
#	"Lämmitystapa",
	"Polttoaine",
#	"Rakennusaine",
#	"Varusteena koneellinen ilmanvaihto",
#	"Perusparannus",
#	"Kunta rakennuttajana",
#	"Energiatehokkuusluokka",
#	"Varusteena aurinkopaneeli",
#	"Tilavuus",
	"Result" # Rakennusala m2
)]

colnames(dat) <- c("City_area", "Time", "Building types in Facta", "Heating types in Facta", "stockBuildingsResult")
dat$Time <- as.numeric(substring(dat$Time, nchar(as.character(dat$Time)) - 3))
dat$Time <- as.numeric(as.character((cut(dat$Time, breaks = c(0, 1885 + 0:26*5), labels = as.character(1885 + 0:26*5)))))
dat$stockBuildingsResult <- as.numeric(as.character(dat$stockBuildingsResult))

build <- tidy(opbase.data("Op_en7115.building_types"))
colnames(build)[colnames(build) == "Result"] <- "Building"

heat <- tidy(opbase.data("Op_en7115.heating_types"))
colnames(heat)[colnames(heat) == "Result"] <- "Heating"

######################
# Korjaus
########################
temp <- as.character(heat$Heating)
temp[temp == "District heating"]  <- "District"
temp[temp == "Light oil"]  <- "Oil"
temp[temp == "Fuel oil"]  <- "Oil"

heat$Heating <- temp
########################################

dat <- merge(merge(dat, build), heat)[c("City_area", "Time", "Building", "Heating", "stockBuildingsResult")]

temp <- aggregate(dat["stockBuildingsResult"], by = dat[c("Time", "Building", "Heating")], FUN =sum)
temp <- temp[!is.na(temp$stockBuildingsResult) , ]

stockBuildings <- Ovariable("stockBuildings", data = temp) # Replace Basel building data with Helsinki data

objects.store(stockBuildings)
cat("Ovariable stockBuildings stored.\n")

library(OpasnetUtils)

# Construction rate is assumed to be 2 % /a from the year 2010 building stock.

# changeBuildings is defined as in Basel but only created now to match Helsinki data.

objects.latest("Op_en7115", code_name = "stockBuildings") # [[Building stock in Helsinki]]

changeBuildings <- stockBuildings
changeBuildings@name <- "changeBuildings"
colnames(changeBuildings@data)[colnames(changeBuildings@data) == "stockBuildingsResult"] <- "changeBuildingsResult"
changeBuildings@data$changeBuildingsResult <- changeBuildings@data$changeBuildingsResult * 0.02
changeBuildings@data$Time <- NULL
changeBuildings@data$Efficiency <- "New"
changeBuildings@data <- merge(changeBuildings@data, data.frame(Time = 2015 + 0:7 * 5))

objects.store(changeBuildings)
cat("Ovariable changeBuildings stored.\n")

library(OpasnetUtils)

renovationRate <- Ovariable('renovationRate',
	dependencies = data.frame(Name = "dummy"),
	formula = function(...) {
		temp <- tidy(opbase.data('Op_en7115', subset = 'Fraction of houses renovated per year'))
		temp$Age <- round(as.numeric(as.character(temp$Age)))
		out <- as.data.frame(approx(
			temp$Age, 
			temp$Result, 
			n = (max(temp$Age) - min(temp$Age) + 1),
			method = "constant"
		))
		colnames(out) <- c("Age", "renovationRateResult")
		out$renovationRateResult <- out$renovationRateResult / 100
		out <- Ovariable("renovationRate", output = out, marginals = c(TRUE, FALSE))
		return(out)
	}
)

objects.store(renovationRate)
cat("Object renovationRate stored.\n")

library(OpasnetUtils)

renovationShares <- Ovariable("renovationShares",
	dependencies = data.frame(Name = "dummy"),
	formula = function(...) {
	out <- Ovariable("raw", ddata = 'Op_en7115', subset = 'Popularity of renovation types')
	out <- findrest((out), cols = "Renovation", total = 100) / 100

	renovationyear <- Ovariable("renovationyear", data = data.frame(
		Startyear = factor(c(2030)),
		Result = 1
	))

	out <- out * renovationyear # renovation shares repeated for every potential renovation year.

	out@output$Renovation <- factor(out@output$Renovation, levels = c(
		"None", 
		"General", 
		"Windows", 
		"Technical systems", 
		"Sheath reform"
	), ordered = TRUE)

	return(out)
	}
)

objects.store(
	renovationShares # Fraction of renovation type when renovation is done.
)

cat("Objects renovationShares stored.\n")

library(OpasnetUtils)

emissionLocations <- Ovariable("emissionLocations", ddata = "Op_en7115", subset = "Emission locations") 
colnames(emissionLocations@data) <- gsub("[ \\.]", "_", colnames(emissionLocations@data))
emissionLocations@data$emissionLocationsResult <- 1

heatingShares <- 1 # This is already in the Basel data.

objects.store(emissionLocations, heatingShares)
cat("Objects emissionsLocations, heatingShares stored.\n")