R/DegreeDays.R
In EntropyEcosystem/DegreeDays: Generator of Cooling Degree Days plot
# coolingDegreeDaysPlot
#
# This is an function
# which generates a cooling Degree day plot.
#
#' @examples
#' DegreeDays::coolingDegreeDaysPlot(datastream,base_temp,surface,area_url,area_name,login_api,building_api,energy_consumption_unit)
#' base_temp <- 21
#' surface<- 3382.6
#' datastream <- "http://hesso-entropy.euprojects.net/api/v1/query/executequery/59e5ca1be7d4380671da0c7b"
#' area_name<-"iig_v2"
#' area_url <- "http://hesso-entropy.euprojects.net//api/v1/building/degreedays"
#' login_api<-"http://hesso-entropy.euprojects.net/api/v1/auth/login"
#' building_api <- "http://hesso-entropy.euprojects.net/api/v1/building/energy_profile"
#' energy_consumption_unit <- "Kwatt"
#' @param datastream entropy datastream
#' @param surface area surface
#' @param base_temp base temperature
#' @param area_url area url
#' @param area_name area name
#' @return plot1 if cooling degree days plot as html
#' @export
coolingDegreeDaysPlot <- function(datastream,base_temp,surface,area_url,area_name,login_api,building_api,energy_consumption_unit){
unit_validator <- check_energy_consumption_unit(energy_consumption_unit)
if (unit_validator==0){return;}
base_temp <- as.numeric(base_temp)
surface <- as.numeric(surface)
df <- jsonlite::stream_in(url(datastream))
dfjson <- jsonlite::fromJSON(jsonlite::toJSON(df))
mydata <- dfjson$nameValuePairs
columnnames <-colnames(mydata)
#Get building energy profile
r <- httr::POST(login_api, body = "{\"username\": \"entropy\",\"password\": \"!entropy!\"}")
authorization_key = httr::headers(r)$authorization
#req <- httr::GET(building_api, httr::add_headers(Authorization = authorization_key))
req <- httr::POST(building_api, body = area_name,httr::add_headers(Authorization = authorization_key))
content <- httr::content(req)
htc <- content$nameValuePairs$HeatTransferCoefficient
print (htc)
print(columnnames)
result = tryCatch({
if(identical(columnnames[grepl('temperature_outdoor',columnnames)], character(0)))
{
print("temperature_outdoor is missing.");
return;
}
}, error = function(e) {
print("temperature_outdoor is missing. Is your query well-formed?");
return;
})
if(identical(columnnames[grepl('temperature_indoor',columnnames)], character(0)))
{
print("temperature_indoor is missing. Is your query well-formed?");
return;
}
consumption_columns <-columnnames[grepl('active_power',columnnames)]
if(identical(consumption_columns, character(0)))
{
print("active_power is missing. Is your query well-formed?");
return;
}
x<-data.frame(mydata$inDateTime$nameValuePairs)
tempout_index <- grep(columnnames[grepl('temperature_outdoor',columnnames)], colnames(mydata))
tempin_index <- grep(columnnames[grepl('temperature_indoor',columnnames)], colnames(mydata))
#if many consumptions aggregate them
if (length(consumption_columns)>1){
power_to_aggregate <- dplyr::select(mydata, consumption_columns)
aggregated_power <- rowSums(power_to_aggregate, na.rm = FALSE)
xy <- data.frame(mydata[tempin_index],mydata[tempout_index],aggregated_power,x)
}else{
power_index <- grep(columnnames[grepl('active_power',columnnames)], colnames(mydata))
xy <- data.frame(mydata[tempin_index],mydata[tempout_index],mydata[power_index],x)
}
xy <- na.omit(xy)
#xy <- outliers::rm.outlier(xy, fill = FALSE, median = FALSE, opposite = FALSE)
colnames(xy) <- c("tempin","tempout","power", "time")
xy <- subset(xy, xy$tempout > -30)
xy <- subset(xy, xy$tempout < 100)
xy$power <- xy$power * as.integer(unit_validator)
summary(xy)
# should we calculate in the followig loop the energy need/baseline????
# Energy_need [kW] = SHTC [kW/[Km2] * cdh [Kh] * surface [m2]/ timestamp_length [h]
# HTC [kW/K] = (energyperformance [kWh/m3] * floor_area [m2] * 3 [m]) / (24 [h/d] * HDD [Kd])
# SHTC [kW/(Km2)] = HTC [kW/K] / floor_area [m2]
# energy_waste[kWh] = SHTC[kW/(Km2) * floor_area[m2] * temp_diff[K] * timestamp_length [h]
# energy_waste[kW] = HTC[kW/K] * temp_diff[K]
for(i in 1:nrow(xy))
{
row <- xy[i, ]
#print(row$time)
mydatetime <- as.POSIXct(row$time)
myhour<-lubridate::hour(mydatetime)
out_diff <- (row$tempout - base_temp)
in_diff <- (row$tempin - base_temp)
temp_diff <- base_temp - row$tempin
if ((out_diff > 0) & (in_diff < 0))
{
if( myhour>20 || myhour<8 || lubridate::wday(mydatetime)==1 || lubridate::wday(mydatetime)==7)
{ row$cdd <- 0}
else{row$cdd <- as.numeric((row$tempout - base_temp) / 24)}
energy_waste_indicative <- temp_diff* htc #measured in kwatt
}
else if ((out_diff > 0) & (in_diff > 0))
{
if( myhour>20 || myhour<8 || lubridate::wday(mydatetime)==1 || lubridate::wday(mydatetime)==7)
{row$cdd <-0}
else{row$cdd <- as.numeric((row$tempout - base_temp) / 24)}
energy_waste_indicative <- 0
}
else if (out_diff < 0)
{
row$cdd <- 0
energy_waste_indicative <- 0
}
xy[i, "cdd"] <- row$cdd
xy[i, "energy_waste"] <- energy_waste_indicative
}
print(summary(xy))
xy$time <- as.POSIXct(xy$time)
# xy$cddconsumption <- xy$cdd / xy$power
# energy need, served as baseline, measured in kW
# xy$cddhtc <- htc * xy$cdd
xy$baseline <- htc * xy$cdd
# plot1: plot the CDD in an hourly basis
plot1 <- ggplot2::qplot(x=xy$time, y=xy$cdd,
data=xy, na.rm=TRUE,
size=I(0.6),
main="Cooling Degree Days (in an hourly basis)",
xlab="Date", ylab="Degree hours (kh)")+
#ggplot2::geom_point(na.rm=TRUE, color="red", size=3, pch=4)+
ggplot2::geom_line(ggplot2::aes(y = xy$cdd, col ="CDD (hourly)"), color="blue") +
ggplot2::scale_x_datetime(date_breaks = "12 hour") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 20, hjust = 1)) +
ggplot2::theme(legend.position="bottom", legend.box = "horizontal")
plot(plot1)
plot33 <- ggplot2::qplot(x=xy$time, y=xy$power,
data=xy, na.rm=TRUE,
size=I(0.6),
main="Real Power vs Forecasted (degree days)",
xlab="Date", ylab="Power (Watt)")+
ggplot2::geom_line(ggplot2::aes(y = xy$power, colour = "Real Power")) +
ggplot2::geom_line(ggplot2::aes(y = xy$baseline*1000, colour = "Baseline")) +
ggplot2::geom_point(y = xy$baseline*1000, na.rm=TRUE, color="blue", size=1, pch=16) +
#ggplot2::geom_line(ggplot2::aes(y = xy$energy_waste*1000, colour = "Energy Waste")) +
#ggplot2::geom_point(y = xy$energy_waste*1000, na.rm=TRUE, color="gray", size=2, pch=16) +
ggplot2::scale_x_datetime(date_breaks = "12 hour") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle =20, hjust = 1)) +
ggplot2::theme(legend.position="bottom", legend.box = "horizontal") +
ggplot2::scale_color_manual(name="",values = c("Real Power"="#00ba38", "Forecasted"="#87CEFA")) + ggplot2::expand_limits(y=0)
# plot(plot33)
plot34 <- ggplot2::qplot(x=xy$time, y=xy$energy_waste,
data=xy, na.rm=TRUE,
size=I(0.6),
main="Indication for Energy Waste (degree days)",
xlab="Date", ylab="Power (Watt)")+
ggplot2::geom_line(ggplot2::aes(y = xy$energy_waste*1000)) +
ggplot2::geom_point(y = xy$energy_waste*1000, na.rm=TRUE, color="cornflowerblue", size=1, pch=16) +
ggplot2::scale_x_datetime(date_breaks = "12 hour") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 20, hjust = 1)) +
ggplot2::expand_limits(y=0)
# Use cowplot for preparing one aligned graph with both figures
#coolingplot2 <- cowplot::plot_grid(plot33, plot34, nrow=2, align="v", rel_heights = c(1.3, 1))
#plot(coolingplot2)
#save plot locally
png(filename="plot0.png")
plot(plot1)
dev.off()
png(filename="plot1.png")
plott <- gridExtra::grid.arrange(plot33, plot34, ncol=1, nrow = 2, heights=c(2,1))
plot(plott)
dev.off()
#png(filename="plot3.png")
#plott <- gridExtra::grid.arrange(plot1,plot33, plot34, ncol=1, nrow = 3, heights=c(1,2,1))
#plot(plott)
#dev.off()
#assosiate degree day plot with area
h <- curl::new_handle()
curl::handle_setform(h,areaname = area_name, file = curl::form_file("plot0.png", "image/png"))
req <- curl::curl_fetch_memory(area_url, handle = h)
h <- curl::new_handle()
curl::handle_setform(h,areaname = area_name, file = curl::form_file("plot1.png", "image/png"))
#req <- curl::curl_fetch_memory("http://localhost:8080/api/v1/building/degreedays", handle = h)
#curl::handle_setform(h,areaname = area_name, file = curl::form_file(plot1))
req <- curl::curl_fetch_memory(area_url, handle = h)
}
# heatingDegreeDaysPlot
#
# This is an function
# which generates a heating Degree day plot.
#
#' @examples
#' DegreeDays::heatingDegreeDaysPlot(datastream,base_temp,surface,area_url,area_name,login_api,building_api,energy_consumption_unit)
#' base_temp <- 24
#' surface<- 3382.6
#' datastream <- "http://hesso-entropy.euprojects.net/api/v1/query/executequery/59e5ca1be7d4380671da0c7b"
#' area_name<-"iig_v2"
#' area_url <- "http://hesso-entropy.euprojects.net//api/v1/building/degreedays"
#' login_api<-"http://hesso-entropy.euprojects.net/api/v1/auth/login"
#' building_api <- "http://hesso-entropy.euprojects.net/api/v1/building/energy_profile"
#' @param datastream entropy datastream
#' @param surface area surface
#' @param base_temp base temperature
#' @param area_url area url
#' @param area_name area name
#' @return plot3 plot3
#' @return xy xy
#' @export
# curl http://212.101.173.76/ocpu/library/DegreeDays/R/heatingDegreeDaysPlot -d "base_temp=21&surface=3382.6&datastream='http://hesso-entropy.euprojects.net/api/v1/query/executequery/59e5ca1be7d4380671da0c7b'&area_name='iig_v2'&area_url='http://hesso-entropy.euprojects.net//api/v1/building/degreedays'&login_api='http://hesso-entropy.euprojects.net/api/v1/auth/login'&building_api='http://hesso-entropy.euprojects.net/api/v1/building/energy_profile'&energy_consumption_unit='Kwatthour'"
heatingDegreeDaysPlot <-function (datastream, base_temp, surface,area_url,area_name,login_api,building_api,energy_consumption_unit) {
unit_validator <- check_energy_consumption_unit(energy_consumption_unit)
if (unit_validator==0){return;}
base_temp <- as.numeric(base_temp)
surface <- as.numeric(surface)
df <- jsonlite::stream_in(url(datastream))
dfjson <- jsonlite::fromJSON(jsonlite::toJSON(df))
mydata <- dfjson$nameValuePairs
#Get building energy profile
r <- httr::POST(login_api, body = "{\"username\": \"entropy\",\"password\": \"!entropy!\"}")
authorization_key = httr::headers(r)$authorization
#req <- httr::GET(bulding_api, httr::add_headers(Authorization = authorization_key))
req <- httr::POST(building_api, body = area_name,httr::add_headers(Authorization = authorization_key))
content <- httr::content(req)
htc <- content$nameValuePairs$HeatTransferCoefficient
print (htc)
columnnames <- colnames(mydata)
if(!("temperature_outdoor" %in% colnames(mydata)))
{
print("temperature_outdoor is missing. Is your query well-formed?");
return;
}
if(!("temperature_indoor" %in% colnames(mydata)))
{
print("temperature_indoor is missing. Is your query well-formed?");
return;
}
if(!("active_power" %in% colnames(mydata)))
{
print("active_power is missing. Is your query well-formed?");
return;
}
consumption_columns <-columnnames[grepl('active_power',columnnames)]
x <- data.frame(mydata$inDateTime$nameValuePairs)
tempout_index <- grep(columnnames[grepl("temperature_outdoor",columnnames)], colnames(mydata))
tempin_index <- grep(columnnames[grepl("temperature_indoor",columnnames)], colnames(mydata))
#if many consumptions aggregate them
if (length(consumption_columns)>1){
power_to_aggregate <- dplyr::select(mydata, consumption_columns)
aggregated_power <- rowSums(power_to_aggregate, na.rm = FALSE)
xy <- data.frame(mydata[tempin_index],mydata[tempout_index],aggregated_power,x)
}else{
power_index <- grep(columnnames[grepl("active_power", columnnames)],colnames(mydata))
xy <- data.frame(mydata[tempin_index], mydata[tempout_index],mydata[power_index], x)
}
xy <- na.omit(xy)
colnames(xy) <- c("tempin", "tempout", "power", "time")
xy <- subset(xy, xy$tempout > -30)
xy <- subset(xy, xy$tempout < 100)
xy$power <- xy$power * as.integer(unit_validator)
summary(xy)
for (i in 1:nrow(xy)) {
row <- xy[i, ]
out_diff <- (row$tempout - base_temp)
in_diff <- (row$tempin - base_temp)
temp_diff <- (row$tempin - base_temp)
print("out_diff")
print(out_diff)
print(in_diff)
print(temp_diff)
mydatetime <- as.POSIXct(row$time)
myhour<-lubridate::hour(mydatetime)
if ((out_diff < 0) & (in_diff > 0)) {
if( myhour>20 || myhour<8 || lubridate::wday(mydatetime)==1 || lubridate::wday(mydatetime)==7)
{ row$hdd <- 0}
else{row$hdd <- as.numeric((base_temp - row$tempout)/24)}
energy_waste_indicative <- temp_diff * htc
}
else if ((out_diff < 0) & (in_diff < 0)) {
if(myhour>20 || myhour<8 || lubridate::wday(mydatetime) == 1 || lubridate::wday(mydatetime) == 7){ row$hdd <- 0}
else{row$hdd <- as.numeric((base_temp - row$tempout)/24)}
energy_waste_indicative <- 0
}
else if ((out_diff > 0)) {
row$hdd <- 0
energy_waste_indicative <- 0
}else {
row$hdd <- 0
energy_waste_indicative <- 0
}
xy[i, "hdd"] <- row$hdd
xy[i, "energy_waste"] <- energy_waste_indicative
}
print(summary(xy))
xy$time <- as.POSIXct(xy$time)
xy$hddconsumption <- xy$hdd / xy$power
# energy need, served as baseline, measured in kW
xy$hddhtc <- htc * xy$hdd
xy$baseline <- htc * xy$hdd
# plot1: plot the HDD in an hourly basis
plot1 <- ggplot2::qplot(x=xy$time, y=xy$hdd,
data=xy, na.rm=TRUE,
size=I(0.6),
main="Heating Degree Days (in an hourly basis)",
xlab="Date", ylab="Degree hours (kh)")+
#ggplot2::geom_point(na.rm=TRUE, color="red", size=3, pch=18)+
ggplot2::geom_line(ggplot2::aes(y = xy$hdd, col ="HDD (hourly)"), color="blue") +
ggplot2::scale_x_datetime(date_breaks = "12 hour") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 20, hjust = 1)) +
ggplot2::theme(legend.position="bottom", legend.box = "horizontal")
plot(plot1)
plot33 <- ggplot2::qplot(x=xy$time, y=xy$power,
data=xy, na.rm=TRUE,
size=I(0.6),
main="Real Power vs Forecasted (degree days)",
xlab="Date", ylab="Power (Watt)")+
ggplot2::geom_line(ggplot2::aes(y = xy$power, colour = "Real Power")) +
ggplot2::geom_line(ggplot2::aes(y = xy$baseline*1000, colour = "Forecasted")) +
ggplot2::geom_point(y = xy$baseline*1000, na.rm=TRUE, color="blue", size=1, pch=16) +
#ggplot2::geom_line(ggplot2::aes(y = xy$energy_waste*1000, colour = "Energy Waste")) +
#ggplot2::geom_point(y = xy$energy_waste*1000, na.rm=TRUE, color="gray", size=2, pch=16) +
ggplot2::scale_x_datetime(date_breaks = "12 hour") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 20, hjust = 1)) +
ggplot2::theme(legend.position="bottom", legend.box = "horizontal") +
ggplot2::scale_color_manual(name="",
values = c("Real Power"="#00ba38", "Forecasted"="#87CEFA")) + ggplot2::expand_limits(y=0)
plot(plot33)
plot34 <- ggplot2::qplot(x=xy$time, y=xy$energy_waste,
data=xy, na.rm=TRUE,
size=I(0.6),
main="Indication for Energy Waste (degree days)",
xlab="Date", ylab="Power (Watt)")+
ggplot2::geom_line(ggplot2::aes(y = xy$energy_waste*1000)) +
ggplot2::geom_point(y = xy$energy_waste*1000, na.rm=TRUE, color="gray", size=1, pch=16) +
ggplot2::scale_x_datetime(date_breaks = "12 hour") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 20, hjust = 1)) +
ggplot2::expand_limits(y=0)
plot(plot34)
# Use cowplot for preparing one aligned graph with both figures
# heatingplot <- cowplot::plot_grid(plot1, plot33, plot34, nrow=3, align="v", rel_heights = c(1, 1.3, 1))
# plot(heatingplot)
#heatingplot2 <- cowplot::plot_grid(plot33, plot34, nrow=2, align="v", rel_heights = c(1.3, 1))
#plot(heatingplot2)
#png(filename="plot1.png")
#gridExtra::grid.arrange(plot1, plot2, ncol=1, nrow = 2)
#cowplot::plot_grid(plot1, plot33, plot34, nrow=3, align="v")
#dev.off()
# #save plot locally
png(filename="plot0.png")
plot(plot1)
dev.off()
png(filename="plot1.png")
plott <- gridExtra::grid.arrange(plot33, plot34, ncol=1, nrow = 2, heights=c(2,1))
plot(plott)
dev.off()
#assosiate degree day plot with area
h <- curl::new_handle()
curl::handle_setform(h,areaname = area_name, file = curl::form_file("plot0.png", "image/png"))
req <- curl::curl_fetch_memory(area_url, handle = h)
h <- curl::new_handle()
curl::handle_setform(h,areaname = area_name, file = curl::form_file("plot1.png", "image/png"))
req <- curl::curl_fetch_memory(area_url, handle = h)
#return(plot3)
}
#' @return 1000, 1 or 0
check_energy_consumption_unit <-function (energy_consumption_unit){
v <- c('Kwatt','Kwatthour','watt','watthour')
if (energy_consumption_unit %in% v){
if (energy_consumption_unit=="Kwatt" || energy_consumption_unit=="watthour"){
result <- "1000"
}else result <- "1"
}else{
print(paste("energy_consumption_unit is not valid",energy_consumption_unit, sep=" "))
result <- "0";
}
return(result)
}
EntropyEcosystem/DegreeDays documentation built on May 9, 2019, 1 a.m.
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# coolingDegreeDaysPlot
#
# This is an function
# which generates a cooling Degree day plot.
#
#' @examples
#' DegreeDays::coolingDegreeDaysPlot(datastream,base_temp,surface,area_url,area_name,login_api,building_api,energy_consumption_unit)
#' base_temp <- 21
#' surface<- 3382.6
#' datastream <- "http://hesso-entropy.euprojects.net/api/v1/query/executequery/59e5ca1be7d4380671da0c7b"
#' area_name<-"iig_v2"
#' area_url <- "http://hesso-entropy.euprojects.net//api/v1/building/degreedays"
#' login_api<-"http://hesso-entropy.euprojects.net/api/v1/auth/login"
#' building_api <- "http://hesso-entropy.euprojects.net/api/v1/building/energy_profile"
#' energy_consumption_unit <- "Kwatt"
#' @param datastream entropy datastream
#' @param surface area surface
#' @param base_temp base temperature
#' @param area_url area url
#' @param area_name area name
#' @return plot1 if cooling degree days plot as html
#' @export
coolingDegreeDaysPlot <- function(datastream,base_temp,surface,area_url,area_name,login_api,building_api,energy_consumption_unit){
unit_validator <- check_energy_consumption_unit(energy_consumption_unit)
if (unit_validator==0){return;}
base_temp <- as.numeric(base_temp)
surface <- as.numeric(surface)
df <- jsonlite::stream_in(url(datastream))
dfjson <- jsonlite::fromJSON(jsonlite::toJSON(df))
mydata <- dfjson$nameValuePairs
columnnames <-colnames(mydata)
#Get building energy profile
r <- httr::POST(login_api, body = "{\"username\": \"entropy\",\"password\": \"!entropy!\"}")
authorization_key = httr::headers(r)$authorization
#req <- httr::GET(building_api, httr::add_headers(Authorization = authorization_key))
req <- httr::POST(building_api, body = area_name,httr::add_headers(Authorization = authorization_key))
content <- httr::content(req)
htc <- content$nameValuePairs$HeatTransferCoefficient
print (htc)
print(columnnames)
result = tryCatch({
if(identical(columnnames[grepl('temperature_outdoor',columnnames)], character(0)))
{
print("temperature_outdoor is missing.");
return;
}
}, error = function(e) {
print("temperature_outdoor is missing. Is your query well-formed?");
return;
})
if(identical(columnnames[grepl('temperature_indoor',columnnames)], character(0)))
{
print("temperature_indoor is missing. Is your query well-formed?");
return;
}
consumption_columns <-columnnames[grepl('active_power',columnnames)]
if(identical(consumption_columns, character(0)))
{
print("active_power is missing. Is your query well-formed?");
return;
}
x<-data.frame(mydata$inDateTime$nameValuePairs)
tempout_index <- grep(columnnames[grepl('temperature_outdoor',columnnames)], colnames(mydata))
tempin_index <- grep(columnnames[grepl('temperature_indoor',columnnames)], colnames(mydata))
#if many consumptions aggregate them
if (length(consumption_columns)>1){
power_to_aggregate <- dplyr::select(mydata, consumption_columns)
aggregated_power <- rowSums(power_to_aggregate, na.rm = FALSE)
xy <- data.frame(mydata[tempin_index],mydata[tempout_index],aggregated_power,x)
}else{
power_index <- grep(columnnames[grepl('active_power',columnnames)], colnames(mydata))
xy <- data.frame(mydata[tempin_index],mydata[tempout_index],mydata[power_index],x)
}
xy <- na.omit(xy)
#xy <- outliers::rm.outlier(xy, fill = FALSE, median = FALSE, opposite = FALSE)
colnames(xy) <- c("tempin","tempout","power", "time")
xy <- subset(xy, xy$tempout > -30)
xy <- subset(xy, xy$tempout < 100)
xy$power <- xy$power * as.integer(unit_validator)
summary(xy)
# should we calculate in the followig loop the energy need/baseline????
# Energy_need [kW] = SHTC [kW/[Km2] * cdh [Kh] * surface [m2]/ timestamp_length [h]
# HTC [kW/K] = (energyperformance [kWh/m3] * floor_area [m2] * 3 [m]) / (24 [h/d] * HDD [Kd])
# SHTC [kW/(Km2)] = HTC [kW/K] / floor_area [m2]
# energy_waste[kWh] = SHTC[kW/(Km2) * floor_area[m2] * temp_diff[K] * timestamp_length [h]
# energy_waste[kW] = HTC[kW/K] * temp_diff[K]
for(i in 1:nrow(xy))
{
row <- xy[i, ]
#print(row$time)
mydatetime <- as.POSIXct(row$time)
myhour<-lubridate::hour(mydatetime)
out_diff <- (row$tempout - base_temp)
in_diff <- (row$tempin - base_temp)
temp_diff <- base_temp - row$tempin
if ((out_diff > 0) & (in_diff < 0))
{
if( myhour>20 || myhour<8 || lubridate::wday(mydatetime)==1 || lubridate::wday(mydatetime)==7)
{ row$cdd <- 0}
else{row$cdd <- as.numeric((row$tempout - base_temp) / 24)}
energy_waste_indicative <- temp_diff* htc #measured in kwatt
}
else if ((out_diff > 0) & (in_diff > 0))
{
if( myhour>20 || myhour<8 || lubridate::wday(mydatetime)==1 || lubridate::wday(mydatetime)==7)
{row$cdd <-0}
else{row$cdd <- as.numeric((row$tempout - base_temp) / 24)}
energy_waste_indicative <- 0
}
else if (out_diff < 0)
{
row$cdd <- 0
energy_waste_indicative <- 0
}
xy[i, "cdd"] <- row$cdd
xy[i, "energy_waste"] <- energy_waste_indicative
}
print(summary(xy))
xy$time <- as.POSIXct(xy$time)
# xy$cddconsumption <- xy$cdd / xy$power
# energy need, served as baseline, measured in kW
# xy$cddhtc <- htc * xy$cdd
xy$baseline <- htc * xy$cdd
# plot1: plot the CDD in an hourly basis
plot1 <- ggplot2::qplot(x=xy$time, y=xy$cdd,
data=xy, na.rm=TRUE,
size=I(0.6),
main="Cooling Degree Days (in an hourly basis)",
xlab="Date", ylab="Degree hours (kh)")+
#ggplot2::geom_point(na.rm=TRUE, color="red", size=3, pch=4)+
ggplot2::geom_line(ggplot2::aes(y = xy$cdd, col ="CDD (hourly)"), color="blue") +
ggplot2::scale_x_datetime(date_breaks = "12 hour") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 20, hjust = 1)) +
ggplot2::theme(legend.position="bottom", legend.box = "horizontal")
plot(plot1)
plot33 <- ggplot2::qplot(x=xy$time, y=xy$power,
data=xy, na.rm=TRUE,
size=I(0.6),
main="Real Power vs Forecasted (degree days)",
xlab="Date", ylab="Power (Watt)")+
ggplot2::geom_line(ggplot2::aes(y = xy$power, colour = "Real Power")) +
ggplot2::geom_line(ggplot2::aes(y = xy$baseline*1000, colour = "Baseline")) +
ggplot2::geom_point(y = xy$baseline*1000, na.rm=TRUE, color="blue", size=1, pch=16) +
#ggplot2::geom_line(ggplot2::aes(y = xy$energy_waste*1000, colour = "Energy Waste")) +
#ggplot2::geom_point(y = xy$energy_waste*1000, na.rm=TRUE, color="gray", size=2, pch=16) +
ggplot2::scale_x_datetime(date_breaks = "12 hour") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle =20, hjust = 1)) +
ggplot2::theme(legend.position="bottom", legend.box = "horizontal") +
ggplot2::scale_color_manual(name="",values = c("Real Power"="#00ba38", "Forecasted"="#87CEFA")) + ggplot2::expand_limits(y=0)
# plot(plot33)
plot34 <- ggplot2::qplot(x=xy$time, y=xy$energy_waste,
data=xy, na.rm=TRUE,
size=I(0.6),
main="Indication for Energy Waste (degree days)",
xlab="Date", ylab="Power (Watt)")+
ggplot2::geom_line(ggplot2::aes(y = xy$energy_waste*1000)) +
ggplot2::geom_point(y = xy$energy_waste*1000, na.rm=TRUE, color="cornflowerblue", size=1, pch=16) +
ggplot2::scale_x_datetime(date_breaks = "12 hour") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 20, hjust = 1)) +
ggplot2::expand_limits(y=0)
# Use cowplot for preparing one aligned graph with both figures
#coolingplot2 <- cowplot::plot_grid(plot33, plot34, nrow=2, align="v", rel_heights = c(1.3, 1))
#plot(coolingplot2)
#save plot locally
png(filename="plot0.png")
plot(plot1)
dev.off()
png(filename="plot1.png")
plott <- gridExtra::grid.arrange(plot33, plot34, ncol=1, nrow = 2, heights=c(2,1))
plot(plott)
dev.off()
#png(filename="plot3.png")
#plott <- gridExtra::grid.arrange(plot1,plot33, plot34, ncol=1, nrow = 3, heights=c(1,2,1))
#plot(plott)
#dev.off()
#assosiate degree day plot with area
h <- curl::new_handle()
curl::handle_setform(h,areaname = area_name, file = curl::form_file("plot0.png", "image/png"))
req <- curl::curl_fetch_memory(area_url, handle = h)
h <- curl::new_handle()
curl::handle_setform(h,areaname = area_name, file = curl::form_file("plot1.png", "image/png"))
#req <- curl::curl_fetch_memory("http://localhost:8080/api/v1/building/degreedays", handle = h)
#curl::handle_setform(h,areaname = area_name, file = curl::form_file(plot1))
req <- curl::curl_fetch_memory(area_url, handle = h)
}
# heatingDegreeDaysPlot
#
# This is an function
# which generates a heating Degree day plot.
#
#' @examples
#' DegreeDays::heatingDegreeDaysPlot(datastream,base_temp,surface,area_url,area_name,login_api,building_api,energy_consumption_unit)
#' base_temp <- 24
#' surface<- 3382.6
#' datastream <- "http://hesso-entropy.euprojects.net/api/v1/query/executequery/59e5ca1be7d4380671da0c7b"
#' area_name<-"iig_v2"
#' area_url <- "http://hesso-entropy.euprojects.net//api/v1/building/degreedays"
#' login_api<-"http://hesso-entropy.euprojects.net/api/v1/auth/login"
#' building_api <- "http://hesso-entropy.euprojects.net/api/v1/building/energy_profile"
#' @param datastream entropy datastream
#' @param surface area surface
#' @param base_temp base temperature
#' @param area_url area url
#' @param area_name area name
#' @return plot3 plot3
#' @return xy xy
#' @export
# curl http://212.101.173.76/ocpu/library/DegreeDays/R/heatingDegreeDaysPlot -d "base_temp=21&surface=3382.6&datastream='http://hesso-entropy.euprojects.net/api/v1/query/executequery/59e5ca1be7d4380671da0c7b'&area_name='iig_v2'&area_url='http://hesso-entropy.euprojects.net//api/v1/building/degreedays'&login_api='http://hesso-entropy.euprojects.net/api/v1/auth/login'&building_api='http://hesso-entropy.euprojects.net/api/v1/building/energy_profile'&energy_consumption_unit='Kwatthour'"
heatingDegreeDaysPlot <-function (datastream, base_temp, surface,area_url,area_name,login_api,building_api,energy_consumption_unit) {
unit_validator <- check_energy_consumption_unit(energy_consumption_unit)
if (unit_validator==0){return;}
base_temp <- as.numeric(base_temp)
surface <- as.numeric(surface)
df <- jsonlite::stream_in(url(datastream))
dfjson <- jsonlite::fromJSON(jsonlite::toJSON(df))
mydata <- dfjson$nameValuePairs
#Get building energy profile
r <- httr::POST(login_api, body = "{\"username\": \"entropy\",\"password\": \"!entropy!\"}")
authorization_key = httr::headers(r)$authorization
#req <- httr::GET(bulding_api, httr::add_headers(Authorization = authorization_key))
req <- httr::POST(building_api, body = area_name,httr::add_headers(Authorization = authorization_key))
content <- httr::content(req)
htc <- content$nameValuePairs$HeatTransferCoefficient
print (htc)
columnnames <- colnames(mydata)
if(!("temperature_outdoor" %in% colnames(mydata)))
{
print("temperature_outdoor is missing. Is your query well-formed?");
return;
}
if(!("temperature_indoor" %in% colnames(mydata)))
{
print("temperature_indoor is missing. Is your query well-formed?");
return;
}
if(!("active_power" %in% colnames(mydata)))
{
print("active_power is missing. Is your query well-formed?");
return;
}
consumption_columns <-columnnames[grepl('active_power',columnnames)]
x <- data.frame(mydata$inDateTime$nameValuePairs)
tempout_index <- grep(columnnames[grepl("temperature_outdoor",columnnames)], colnames(mydata))
tempin_index <- grep(columnnames[grepl("temperature_indoor",columnnames)], colnames(mydata))
#if many consumptions aggregate them
if (length(consumption_columns)>1){
power_to_aggregate <- dplyr::select(mydata, consumption_columns)
aggregated_power <- rowSums(power_to_aggregate, na.rm = FALSE)
xy <- data.frame(mydata[tempin_index],mydata[tempout_index],aggregated_power,x)
}else{
power_index <- grep(columnnames[grepl("active_power", columnnames)],colnames(mydata))
xy <- data.frame(mydata[tempin_index], mydata[tempout_index],mydata[power_index], x)
}
xy <- na.omit(xy)
colnames(xy) <- c("tempin", "tempout", "power", "time")
xy <- subset(xy, xy$tempout > -30)
xy <- subset(xy, xy$tempout < 100)
xy$power <- xy$power * as.integer(unit_validator)
summary(xy)
for (i in 1:nrow(xy)) {
row <- xy[i, ]
out_diff <- (row$tempout - base_temp)
in_diff <- (row$tempin - base_temp)
temp_diff <- (row$tempin - base_temp)
print("out_diff")
print(out_diff)
print(in_diff)
print(temp_diff)
mydatetime <- as.POSIXct(row$time)
myhour<-lubridate::hour(mydatetime)
if ((out_diff < 0) & (in_diff > 0)) {
if( myhour>20 || myhour<8 || lubridate::wday(mydatetime)==1 || lubridate::wday(mydatetime)==7)
{ row$hdd <- 0}
else{row$hdd <- as.numeric((base_temp - row$tempout)/24)}
energy_waste_indicative <- temp_diff * htc
}
else if ((out_diff < 0) & (in_diff < 0)) {
if(myhour>20 || myhour<8 || lubridate::wday(mydatetime) == 1 || lubridate::wday(mydatetime) == 7){ row$hdd <- 0}
else{row$hdd <- as.numeric((base_temp - row$tempout)/24)}
energy_waste_indicative <- 0
}
else if ((out_diff > 0)) {
row$hdd <- 0
energy_waste_indicative <- 0
}else {
row$hdd <- 0
energy_waste_indicative <- 0
}
xy[i, "hdd"] <- row$hdd
xy[i, "energy_waste"] <- energy_waste_indicative
}
print(summary(xy))
xy$time <- as.POSIXct(xy$time)
xy$hddconsumption <- xy$hdd / xy$power
# energy need, served as baseline, measured in kW
xy$hddhtc <- htc * xy$hdd
xy$baseline <- htc * xy$hdd
# plot1: plot the HDD in an hourly basis
plot1 <- ggplot2::qplot(x=xy$time, y=xy$hdd,
data=xy, na.rm=TRUE,
size=I(0.6),
main="Heating Degree Days (in an hourly basis)",
xlab="Date", ylab="Degree hours (kh)")+
#ggplot2::geom_point(na.rm=TRUE, color="red", size=3, pch=18)+
ggplot2::geom_line(ggplot2::aes(y = xy$hdd, col ="HDD (hourly)"), color="blue") +
ggplot2::scale_x_datetime(date_breaks = "12 hour") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 20, hjust = 1)) +
ggplot2::theme(legend.position="bottom", legend.box = "horizontal")
plot(plot1)
plot33 <- ggplot2::qplot(x=xy$time, y=xy$power,
data=xy, na.rm=TRUE,
size=I(0.6),
main="Real Power vs Forecasted (degree days)",
xlab="Date", ylab="Power (Watt)")+
ggplot2::geom_line(ggplot2::aes(y = xy$power, colour = "Real Power")) +
ggplot2::geom_line(ggplot2::aes(y = xy$baseline*1000, colour = "Forecasted")) +
ggplot2::geom_point(y = xy$baseline*1000, na.rm=TRUE, color="blue", size=1, pch=16) +
#ggplot2::geom_line(ggplot2::aes(y = xy$energy_waste*1000, colour = "Energy Waste")) +
#ggplot2::geom_point(y = xy$energy_waste*1000, na.rm=TRUE, color="gray", size=2, pch=16) +
ggplot2::scale_x_datetime(date_breaks = "12 hour") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 20, hjust = 1)) +
ggplot2::theme(legend.position="bottom", legend.box = "horizontal") +
ggplot2::scale_color_manual(name="",
values = c("Real Power"="#00ba38", "Forecasted"="#87CEFA")) + ggplot2::expand_limits(y=0)
plot(plot33)
plot34 <- ggplot2::qplot(x=xy$time, y=xy$energy_waste,
data=xy, na.rm=TRUE,
size=I(0.6),
main="Indication for Energy Waste (degree days)",
xlab="Date", ylab="Power (Watt)")+
ggplot2::geom_line(ggplot2::aes(y = xy$energy_waste*1000)) +
ggplot2::geom_point(y = xy$energy_waste*1000, na.rm=TRUE, color="gray", size=1, pch=16) +
ggplot2::scale_x_datetime(date_breaks = "12 hour") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 20, hjust = 1)) +
ggplot2::expand_limits(y=0)
plot(plot34)
# Use cowplot for preparing one aligned graph with both figures
# heatingplot <- cowplot::plot_grid(plot1, plot33, plot34, nrow=3, align="v", rel_heights = c(1, 1.3, 1))
# plot(heatingplot)
#heatingplot2 <- cowplot::plot_grid(plot33, plot34, nrow=2, align="v", rel_heights = c(1.3, 1))
#plot(heatingplot2)
#png(filename="plot1.png")
#gridExtra::grid.arrange(plot1, plot2, ncol=1, nrow = 2)
#cowplot::plot_grid(plot1, plot33, plot34, nrow=3, align="v")
#dev.off()
# #save plot locally
png(filename="plot0.png")
plot(plot1)
dev.off()
png(filename="plot1.png")
plott <- gridExtra::grid.arrange(plot33, plot34, ncol=1, nrow = 2, heights=c(2,1))
plot(plott)
dev.off()
#assosiate degree day plot with area
h <- curl::new_handle()
curl::handle_setform(h,areaname = area_name, file = curl::form_file("plot0.png", "image/png"))
req <- curl::curl_fetch_memory(area_url, handle = h)
h <- curl::new_handle()
curl::handle_setform(h,areaname = area_name, file = curl::form_file("plot1.png", "image/png"))
req <- curl::curl_fetch_memory(area_url, handle = h)
#return(plot3)
}
#' @return 1000, 1 or 0
check_energy_consumption_unit <-function (energy_consumption_unit){
v <- c('Kwatt','Kwatthour','watt','watthour')
if (energy_consumption_unit %in% v){
if (energy_consumption_unit=="Kwatt" || energy_consumption_unit=="watthour"){
result <- "1000"
}else result <- "1"
}else{
print(paste("energy_consumption_unit is not valid",energy_consumption_unit, sep=" "))
result <- "0";
}
return(result)
}
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