server.R
In mlguys/ShinySolarCalculator: Solar Energy Calculator
# *------------------------------------------------------------------
# | PROGRAM NAME: Solar Energy Calculator
# | DATE: Feb 1 2016
# | CREATED BY: La Minh Hoang
# | PROJECT FILE: server.R
# | CONTACT: hoangrobin@gmail.com
# *----------------------------------------------------------------
# | PURPOSE:
# | -Provide server script for shiny package
# *------------------------------------------------------------------
# | References: http://shiny.rstudio.com/tutorial/
# |
# |
# *------------------------------------------------------------------
# | UPDATES:
# | -Feb 1 2016: Added comments
# |
# *------------------------------------------------------------------
library(shiny)
library(scatterplot3d)
source("R/suncalculator.R",chdir=T)
shinyServer(function(input, output) {
data <- reactiveValues(
date = Sys.Date(),
# hour = 8,
# minute = 0,
# year = as.numeric(format(Sys.Date(), "%Y")),
# month = as.numeric(format(Sys.Date(), "%m")),
lat = 0,
long = 0,
gmt = 0,
tilt = 45,
azi = 180,
sealevel = 0
)
totalSolarEnergyDay <- reactiveValues(data = solarOneDay(
as.numeric(format(Sys.Date(), "%Y")),
as.numeric(format(Sys.Date(), "%m")),
as.numeric(format(Sys.Date(), "%d")),
0,
0,
0,
45,
180,
0
))
dataMonth <- reactiveValues(
year = as.numeric(format(Sys.Date(), "%Y")),
month = as.numeric(format(Sys.Date(), "%m")),
lat = 0,
long = 0,
gmt = 0,
tilt = 45,
azi = 180,
sealevel = 0
)
totalSolarEnergyMonth <-
reactiveValues(data = solarOneMonth(as.numeric(format(Sys.Date(
), "%Y")),
as.numeric(format(Sys.Date(
), "%m")),
0,
0,
0,
45,
180,
0))
dataYear <- reactiveValues(
year = as.numeric(format(Sys.Date(), "%Y")),
lat = 0,
long = 0,
gmt = 0,
tilt = 45,
azi = 180,
sealevel = 0
)
totalSolarEnergyYear <-
reactiveValues(data = solarOneYear(as.numeric(format(Sys.Date(
), "%Y")),
0,
0,
0,
45,
180,
0))
###Data for optimal
matrix = NULL;
for (i in 1:7) {
for (j in 1:16) {
matrix = rbind(matrix,c((i - 1) * 15,(j - 1) * 22.5, 0))
}
}
df <-
data.frame(
tilt = matrix[,1], azi = matrix[,2], solar = matrix[,3], fromNorth = NA
)
df$fromNorth[df$azi == 0] <- "North"
df$fromNorth[df$azi == 22.5] <- "North-Northeast"
df$fromNorth[df$azi == 45] <- "Northeast"
df$fromNorth[df$azi == 67.5] <- "East-Northeast"
df$fromNorth[df$azi == 90] <- "East"
df$fromNorth[df$azi == 112.5] <- "East-Southeast"
df$fromNorth[df$azi == 135] <- "Southeast"
df$fromNorth[df$azi == 157.5] <- "South-Southeast"
df$fromNorth[df$azi == 180] <- "South"
df$fromNorth[df$azi == 202.5] <- "South-Southwest"
df$fromNorth[df$azi == 225] <- "Southwest"
df$fromNorth[df$azi == 247.5] <- "West-Southwest"
df$fromNorth[df$azi == 270] <- "West"
df$fromNorth[df$azi == 292.5] <- "West-Northwest"
df$fromNorth[df$azi == 315] <- "Northwest"
df$fromNorth[df$azi == 337.5] <- "North-Northwest"
dataOptimalYear <- reactiveValues(
data = df,
year = as.numeric(format(Sys.Date(), "%Y")),
lat = 0,
long = 0,
gmt = 0,
sealevel = 0
)
###Day Calculation###
observeEvent(input$actCalculateDay, {
data$date <- input$dateDay
})
# observeEvent(input$actCalculateDay, { data$hour <- input$hourslider })
# observeEvent(input$actCalculateDay, { data$minute <- input$minuteslider })
observeEvent(input$actCalculateDay, {
data$lat <- input$latDay
})
observeEvent(input$actCalculateDay, {
data$long <- input$longDay
})
observeEvent(input$actCalculateDay, {
data$gmt <- input$gmtsliderDay
})
observeEvent(input$actCalculateDay, {
data$tilt <- input$tiltsliderDay
})
observeEvent(input$actCalculateDay, {
data$azi <- input$aziDay
})
observeEvent(input$actCalculateDay, {
data$sealevel <- input$sealevelDay
})
observeEvent(input$actCalculateDay, {
totalSolarEnergyDay$data <- solarOneDay(
as.numeric(format(data$date, "%Y")),
as.numeric(format(data$date, "%m")),
as.numeric(format(data$date, "%d")),
data$lat,
data$long,
data$gmt,
data$tilt,
data$azi,
data$sealevel
)
})
output$totalEnergyDay <- renderUI({
withMathJax(
"$$\\text{Total solar energy received on ", format(data$date, "%A %B %d %Y") ,": }", round(totalSolarEnergyDay$data[1], digits =
2) , "\\text{ }kW/m^2/day$$"
)
})
#Generate bar plot
output$plotDay <- renderPlot({
labelsY = parse(text = paste("kW/m", "^2"))
par(mar = c(5,6,4,2) + 0.1)
barplot(
totalSolarEnergyDay$data[2:length(totalSolarEnergyDay$data)],main = "Solar Energy in one day",xlab =
"hour of day", ylab = labelsY,names.arg = 1:24
)
})
#Generate a summary of the data
output$summaryDay <- renderPrint({
summary(totalSolarEnergyDay$data[2:length(totalSolarEnergyDay$data)])
})
# Generate an HTML table view of the data
output$tableDay <- renderTable({
tableSolar <-
cbind(totalSolarEnergyDay$data[2:length(totalSolarEnergyDay$data)]);
colnames(tableSolar, do.NULL = FALSE)
colnames(tableSolar) <- c("Solar Energy")
rownames(tableSolar) <-
rownames(tableSolar, do.NULL = FALSE, prefix = "Hour.")
tableSolar
})
###Day Calculation###
###Month Calculation###
# observeEvent(input$actCalculateMonth, {
# data$date <- input$dateMonth
# })
# observeEvent(input$actCalculateDay, { data$hour <- input$hourslider })
# observeEvent(input$actCalculateDay, { data$minute <- input$minuteslider })
observeEvent(input$actCalculateMonth, {
dataMonth$year <- input$yearMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$month <- input$monthMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$lat <- input$latMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$long <- input$longMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$gmt <- input$gmtsliderMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$tilt <- input$tiltsliderMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$azi <- input$aziMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$sealevel <- input$sealevelMonth
})
observeEvent(input$actCalculateMonth, {
totalSolarEnergyMonth$data <- solarOneMonth(
dataMonth$year,
dataMonth$month,
dataMonth$lat,
dataMonth$long,
dataMonth$gmt,
dataMonth$tilt,
dataMonth$azi,
dataMonth$sealevel
)
})
output$totalEnergyMonth <- renderUI({
date = as.Date(paste(dataMonth$year,dataMonth$month,1,sep = "-"));
withMathJax(
"$$\\text{Total solar energy received in ", format(date, "%B %Y") ,": }", round(totalSolarEnergyMonth$data[1], digits =
2) , "\\text{ }kW/m^2/month$$"
)
})
#Generate bar plot
output$plotMonth <- renderPlot({
labelsY = parse(text = paste("kW/m", "^2","/day"))
par(mar = c(5,6,4,2) + 0.1)
barplot(
totalSolarEnergyMonth$data[2:length(totalSolarEnergyMonth$data)],main = "Solar Energy in one month",xlab =
"day of month", ylab = labelsY,names.arg = 1:(length(totalSolarEnergyMonth$data) -
1)
)
})
#Generate a summary of the data
output$summaryMonth <- renderPrint({
summary(totalSolarEnergyMonth$data[2:length(totalSolarEnergyMonth$data)])
})
# Generate an HTML table view of the data
output$tableMonth <- renderTable({
tableSolar <-
cbind(totalSolarEnergyMonth$data[2:length(totalSolarEnergyMonth$data)]);
colnames(tableSolar, do.NULL = FALSE)
colnames(tableSolar) <- c("Solar Energy")
rownames(tableSolar) <-
rownames(tableSolar, do.NULL = FALSE, prefix = "Day.")
tableSolar
})
###Month Calculation###
###Year Calculation###
observeEvent(input$actCalculateYear, {
dataYear$year <- input$yearYear
})
observeEvent(input$actCalculateYear, {
dataYear$lat <- input$latYear
})
observeEvent(input$actCalculateYear, {
dataYear$long <- input$longYear
})
observeEvent(input$actCalculateYear, {
dataYear$gmt <- input$gmtsliderYear
})
observeEvent(input$actCalculateYear, {
dataYear$tilt <- input$tiltsliderYear
})
observeEvent(input$actCalculateYear, {
dataYear$azi <- input$aziYear
})
observeEvent(input$actCalculateYear, {
dataYear$sealevel <- input$sealevelYear
})
observeEvent(input$actCalculateYear, {
totalSolarEnergyYear$data <- solarOneYear(
dataYear$year,
dataYear$lat,
dataYear$long,
dataYear$gmt,
dataYear$tilt,
dataYear$azi,
dataYear$sealevel
)
})
#data for Optimal
###Year Calculation###
observeEvent(input$actCalculateOptimal, {
dataOptimalYear$year <- input$yearOptimal
})
observeEvent(input$actCalculateOptimal, {
dataOptimalYear$lat <- input$latOptimal
})
observeEvent(input$actCalculateOptimal, {
dataOptimalYear$long <- input$longOptimal
})
observeEvent(input$actCalculateOptimal, {
dataOptimalYear$gmt <- input$gmtsliderOptimal
})
observeEvent(input$actCalculateOptimal, {
dataOptimalYear$sealevel <- input$sealevelOptimal
})
observeEvent(input$actCalculateOptimal, {
#print(paste(dataOptimalYear$year," ",dataOptimalYear$lat," ",dataOptimalYear$long," ",dataOptimalYear$gmt," ",dataOptimalYear$sealevel))
# Create a Progress object
progress <- shiny::Progress$new()
progress$set(message = "Computing data",
detail = 'This may take a while...', value = 0)
# Close the progress when this reactive exits (even if there's an error)
on.exit(progress$close())
dataOptimalYear$data <-
findOptimalTiltAngleYear(
dataOptimalYear$year,
dataOptimalYear$lat,
dataOptimalYear$long,
dataOptimalYear$gmt,
dataOptimalYear$sealevel
)
})
output$totalEnergyYear <- renderUI({
date = as.Date(paste(dataYear$year,1,1,sep = "-"));
withMathJax(
"$$\\text{Total solar energy received in ", format(date, "%Y") ,": }", round(totalSolarEnergyYear$data[1], digits =
2) , "\\text{ }kW/m^2/year$$"
)
})
#Generate bar plot
output$plotYear <- renderPlot({
labelsY = parse(text = paste("kW/m", "^2","/day"))
par(mar = c(5,6,4,2) + 0.1)
barplot(
totalSolarEnergyYear$data[2:length(totalSolarEnergyYear$data)],main = paste("Solar Energy in year", dataYear$year),xlab =
"day of year", ylab = labelsY,names.arg = 1:(length(totalSolarEnergyYear$data) -
1)
)
})
#Generate a summary of the data
output$summaryYear <- renderPrint({
summary(totalSolarEnergyYear$data[2:length(totalSolarEnergyYear$data)])
})
# Generate an HTML table view of the data
output$tableYear <- renderTable({
tableSolar <-
cbind(totalSolarEnergyYear$data[2:length(totalSolarEnergyYear$data)]);
colnames(tableSolar, do.NULL = FALSE)
colnames(tableSolar) <- c("Solar Energy")
rownames(tableSolar) <-
rownames(tableSolar, do.NULL = FALSE, prefix = "Day.")
tableSolar
})
#Optimal Angle Year
output$plotOptimal <- renderPlot({
# Create a Progress object
progress <- shiny::Progress$new()
progress$set(message = "Drawing plot", value = 0)
# Close the progress when this reactive exits (even if there's an error)
on.exit(progress$close())
df <- dataOptimalYear$data
labelsZ = parse(text = paste("kW/m", "^2","/year"))
with(df, {
s3d <- scatterplot3d(
tilt, azi, solar, # x y and z axis
pch = 19, # circle color indicates no. of cylinders
type = "h", lty.hplot = 2, # lines to the horizontal plane
scale.y = .75, # scale y axis (reduce by 25%)
main = "Solar Energy by Module Tilt and Azimuth angle",
xlab = "Tilt Angle (degree)",
ylab = "Module Azimuth Angle (degree)",
zlab = labelsZ,
highlight.3d = TRUE
)
s3d.coords <- s3d$xyz.convert(tilt, azi, solar)
# text(s3d.coords$x, s3d.coords$y, # x and y coordinates
# labels=row.names(df), # text to plot
# pos=4, cex=.5) # shrink text 50% and place to right of points)
# add the legend
# legend("topleft", inset=.05, # location and inset
# bty="n", cex=.5, # suppress legend box, shrink text 50%
# title="Solar Energy",
# c(">1500", "1500-1000", "1000-500","500-0"), fill=c("red", "orange","green","blue"))
fit <- lm(solar ~ tilt + azi)
s3d$plane3d(fit)
})
#Generate a summary of the optimal data
output$summaryOptimal <- renderPrint({
summary(dataOptimalYear$data)
})
# Generate an HTML table view of the optimal data
output$tableOptimal <- renderTable({
dataOptimalYear$data
})
output$textOptimal <- renderUI({
df <- dataOptimalYear$data
optimalAzi <- df$azi[df$solar == max(df$solar)][1]
optimalTilt <- df$tilt[df$solar == max(df$solar)][1]
facing <- df$fromNorth[df$azi == optimalAzi][1]
maxSolar <- max(df$solar)[1]
# withMathJax(
# "$$\\text{Total solar energy received in ", format(date, "%Y") ,": }", round(totalSolarEnergyYear$data[1], digits =
# 2) , "\\text{ }kW/m^2/year$$"
# )
withMathJax(
helpText("Optimal Tilt Angle is :$$", optimalTilt,"^o$$"),
helpText("Optimal Module Azimuth Angle is :$$",optimalAzi,"^o$$"),
helpText("The direction the module will face is:$$", facing,"$$"),
helpText(
"Maximum Solar Energy output from module according to optimal angles is:$$", round(maxSolar,digits = 2),"\\text{ }kW/m^2/year$$"
)
)
})
})
###Year Calculation###
})
mlguys/ShinySolarCalculator documentation built on May 23, 2019, 2:09 a.m.
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# *------------------------------------------------------------------
# | PROGRAM NAME: Solar Energy Calculator
# | DATE: Feb 1 2016
# | CREATED BY: La Minh Hoang
# | PROJECT FILE: server.R
# | CONTACT: hoangrobin@gmail.com
# *----------------------------------------------------------------
# | PURPOSE:
# | -Provide server script for shiny package
# *------------------------------------------------------------------
# | References: http://shiny.rstudio.com/tutorial/
# |
# |
# *------------------------------------------------------------------
# | UPDATES:
# | -Feb 1 2016: Added comments
# |
# *------------------------------------------------------------------
library(shiny)
library(scatterplot3d)
source("R/suncalculator.R",chdir=T)
shinyServer(function(input, output) {
data <- reactiveValues(
date = Sys.Date(),
# hour = 8,
# minute = 0,
# year = as.numeric(format(Sys.Date(), "%Y")),
# month = as.numeric(format(Sys.Date(), "%m")),
lat = 0,
long = 0,
gmt = 0,
tilt = 45,
azi = 180,
sealevel = 0
)
totalSolarEnergyDay <- reactiveValues(data = solarOneDay(
as.numeric(format(Sys.Date(), "%Y")),
as.numeric(format(Sys.Date(), "%m")),
as.numeric(format(Sys.Date(), "%d")),
0,
0,
0,
45,
180,
0
))
dataMonth <- reactiveValues(
year = as.numeric(format(Sys.Date(), "%Y")),
month = as.numeric(format(Sys.Date(), "%m")),
lat = 0,
long = 0,
gmt = 0,
tilt = 45,
azi = 180,
sealevel = 0
)
totalSolarEnergyMonth <-
reactiveValues(data = solarOneMonth(as.numeric(format(Sys.Date(
), "%Y")),
as.numeric(format(Sys.Date(
), "%m")),
0,
0,
0,
45,
180,
0))
dataYear <- reactiveValues(
year = as.numeric(format(Sys.Date(), "%Y")),
lat = 0,
long = 0,
gmt = 0,
tilt = 45,
azi = 180,
sealevel = 0
)
totalSolarEnergyYear <-
reactiveValues(data = solarOneYear(as.numeric(format(Sys.Date(
), "%Y")),
0,
0,
0,
45,
180,
0))
###Data for optimal
matrix = NULL;
for (i in 1:7) {
for (j in 1:16) {
matrix = rbind(matrix,c((i - 1) * 15,(j - 1) * 22.5, 0))
}
}
df <-
data.frame(
tilt = matrix[,1], azi = matrix[,2], solar = matrix[,3], fromNorth = NA
)
df$fromNorth[df$azi == 0] <- "North"
df$fromNorth[df$azi == 22.5] <- "North-Northeast"
df$fromNorth[df$azi == 45] <- "Northeast"
df$fromNorth[df$azi == 67.5] <- "East-Northeast"
df$fromNorth[df$azi == 90] <- "East"
df$fromNorth[df$azi == 112.5] <- "East-Southeast"
df$fromNorth[df$azi == 135] <- "Southeast"
df$fromNorth[df$azi == 157.5] <- "South-Southeast"
df$fromNorth[df$azi == 180] <- "South"
df$fromNorth[df$azi == 202.5] <- "South-Southwest"
df$fromNorth[df$azi == 225] <- "Southwest"
df$fromNorth[df$azi == 247.5] <- "West-Southwest"
df$fromNorth[df$azi == 270] <- "West"
df$fromNorth[df$azi == 292.5] <- "West-Northwest"
df$fromNorth[df$azi == 315] <- "Northwest"
df$fromNorth[df$azi == 337.5] <- "North-Northwest"
dataOptimalYear <- reactiveValues(
data = df,
year = as.numeric(format(Sys.Date(), "%Y")),
lat = 0,
long = 0,
gmt = 0,
sealevel = 0
)
###Day Calculation###
observeEvent(input$actCalculateDay, {
data$date <- input$dateDay
})
# observeEvent(input$actCalculateDay, { data$hour <- input$hourslider })
# observeEvent(input$actCalculateDay, { data$minute <- input$minuteslider })
observeEvent(input$actCalculateDay, {
data$lat <- input$latDay
})
observeEvent(input$actCalculateDay, {
data$long <- input$longDay
})
observeEvent(input$actCalculateDay, {
data$gmt <- input$gmtsliderDay
})
observeEvent(input$actCalculateDay, {
data$tilt <- input$tiltsliderDay
})
observeEvent(input$actCalculateDay, {
data$azi <- input$aziDay
})
observeEvent(input$actCalculateDay, {
data$sealevel <- input$sealevelDay
})
observeEvent(input$actCalculateDay, {
totalSolarEnergyDay$data <- solarOneDay(
as.numeric(format(data$date, "%Y")),
as.numeric(format(data$date, "%m")),
as.numeric(format(data$date, "%d")),
data$lat,
data$long,
data$gmt,
data$tilt,
data$azi,
data$sealevel
)
})
output$totalEnergyDay <- renderUI({
withMathJax(
"$$\\text{Total solar energy received on ", format(data$date, "%A %B %d %Y") ,": }", round(totalSolarEnergyDay$data[1], digits =
2) , "\\text{ }kW/m^2/day$$"
)
})
#Generate bar plot
output$plotDay <- renderPlot({
labelsY = parse(text = paste("kW/m", "^2"))
par(mar = c(5,6,4,2) + 0.1)
barplot(
totalSolarEnergyDay$data[2:length(totalSolarEnergyDay$data)],main = "Solar Energy in one day",xlab =
"hour of day", ylab = labelsY,names.arg = 1:24
)
})
#Generate a summary of the data
output$summaryDay <- renderPrint({
summary(totalSolarEnergyDay$data[2:length(totalSolarEnergyDay$data)])
})
# Generate an HTML table view of the data
output$tableDay <- renderTable({
tableSolar <-
cbind(totalSolarEnergyDay$data[2:length(totalSolarEnergyDay$data)]);
colnames(tableSolar, do.NULL = FALSE)
colnames(tableSolar) <- c("Solar Energy")
rownames(tableSolar) <-
rownames(tableSolar, do.NULL = FALSE, prefix = "Hour.")
tableSolar
})
###Day Calculation###
###Month Calculation###
# observeEvent(input$actCalculateMonth, {
# data$date <- input$dateMonth
# })
# observeEvent(input$actCalculateDay, { data$hour <- input$hourslider })
# observeEvent(input$actCalculateDay, { data$minute <- input$minuteslider })
observeEvent(input$actCalculateMonth, {
dataMonth$year <- input$yearMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$month <- input$monthMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$lat <- input$latMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$long <- input$longMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$gmt <- input$gmtsliderMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$tilt <- input$tiltsliderMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$azi <- input$aziMonth
})
observeEvent(input$actCalculateMonth, {
dataMonth$sealevel <- input$sealevelMonth
})
observeEvent(input$actCalculateMonth, {
totalSolarEnergyMonth$data <- solarOneMonth(
dataMonth$year,
dataMonth$month,
dataMonth$lat,
dataMonth$long,
dataMonth$gmt,
dataMonth$tilt,
dataMonth$azi,
dataMonth$sealevel
)
})
output$totalEnergyMonth <- renderUI({
date = as.Date(paste(dataMonth$year,dataMonth$month,1,sep = "-"));
withMathJax(
"$$\\text{Total solar energy received in ", format(date, "%B %Y") ,": }", round(totalSolarEnergyMonth$data[1], digits =
2) , "\\text{ }kW/m^2/month$$"
)
})
#Generate bar plot
output$plotMonth <- renderPlot({
labelsY = parse(text = paste("kW/m", "^2","/day"))
par(mar = c(5,6,4,2) + 0.1)
barplot(
totalSolarEnergyMonth$data[2:length(totalSolarEnergyMonth$data)],main = "Solar Energy in one month",xlab =
"day of month", ylab = labelsY,names.arg = 1:(length(totalSolarEnergyMonth$data) -
1)
)
})
#Generate a summary of the data
output$summaryMonth <- renderPrint({
summary(totalSolarEnergyMonth$data[2:length(totalSolarEnergyMonth$data)])
})
# Generate an HTML table view of the data
output$tableMonth <- renderTable({
tableSolar <-
cbind(totalSolarEnergyMonth$data[2:length(totalSolarEnergyMonth$data)]);
colnames(tableSolar, do.NULL = FALSE)
colnames(tableSolar) <- c("Solar Energy")
rownames(tableSolar) <-
rownames(tableSolar, do.NULL = FALSE, prefix = "Day.")
tableSolar
})
###Month Calculation###
###Year Calculation###
observeEvent(input$actCalculateYear, {
dataYear$year <- input$yearYear
})
observeEvent(input$actCalculateYear, {
dataYear$lat <- input$latYear
})
observeEvent(input$actCalculateYear, {
dataYear$long <- input$longYear
})
observeEvent(input$actCalculateYear, {
dataYear$gmt <- input$gmtsliderYear
})
observeEvent(input$actCalculateYear, {
dataYear$tilt <- input$tiltsliderYear
})
observeEvent(input$actCalculateYear, {
dataYear$azi <- input$aziYear
})
observeEvent(input$actCalculateYear, {
dataYear$sealevel <- input$sealevelYear
})
observeEvent(input$actCalculateYear, {
totalSolarEnergyYear$data <- solarOneYear(
dataYear$year,
dataYear$lat,
dataYear$long,
dataYear$gmt,
dataYear$tilt,
dataYear$azi,
dataYear$sealevel
)
})
#data for Optimal
###Year Calculation###
observeEvent(input$actCalculateOptimal, {
dataOptimalYear$year <- input$yearOptimal
})
observeEvent(input$actCalculateOptimal, {
dataOptimalYear$lat <- input$latOptimal
})
observeEvent(input$actCalculateOptimal, {
dataOptimalYear$long <- input$longOptimal
})
observeEvent(input$actCalculateOptimal, {
dataOptimalYear$gmt <- input$gmtsliderOptimal
})
observeEvent(input$actCalculateOptimal, {
dataOptimalYear$sealevel <- input$sealevelOptimal
})
observeEvent(input$actCalculateOptimal, {
#print(paste(dataOptimalYear$year," ",dataOptimalYear$lat," ",dataOptimalYear$long," ",dataOptimalYear$gmt," ",dataOptimalYear$sealevel))
# Create a Progress object
progress <- shiny::Progress$new()
progress$set(message = "Computing data",
detail = 'This may take a while...', value = 0)
# Close the progress when this reactive exits (even if there's an error)
on.exit(progress$close())
dataOptimalYear$data <-
findOptimalTiltAngleYear(
dataOptimalYear$year,
dataOptimalYear$lat,
dataOptimalYear$long,
dataOptimalYear$gmt,
dataOptimalYear$sealevel
)
})
output$totalEnergyYear <- renderUI({
date = as.Date(paste(dataYear$year,1,1,sep = "-"));
withMathJax(
"$$\\text{Total solar energy received in ", format(date, "%Y") ,": }", round(totalSolarEnergyYear$data[1], digits =
2) , "\\text{ }kW/m^2/year$$"
)
})
#Generate bar plot
output$plotYear <- renderPlot({
labelsY = parse(text = paste("kW/m", "^2","/day"))
par(mar = c(5,6,4,2) + 0.1)
barplot(
totalSolarEnergyYear$data[2:length(totalSolarEnergyYear$data)],main = paste("Solar Energy in year", dataYear$year),xlab =
"day of year", ylab = labelsY,names.arg = 1:(length(totalSolarEnergyYear$data) -
1)
)
})
#Generate a summary of the data
output$summaryYear <- renderPrint({
summary(totalSolarEnergyYear$data[2:length(totalSolarEnergyYear$data)])
})
# Generate an HTML table view of the data
output$tableYear <- renderTable({
tableSolar <-
cbind(totalSolarEnergyYear$data[2:length(totalSolarEnergyYear$data)]);
colnames(tableSolar, do.NULL = FALSE)
colnames(tableSolar) <- c("Solar Energy")
rownames(tableSolar) <-
rownames(tableSolar, do.NULL = FALSE, prefix = "Day.")
tableSolar
})
#Optimal Angle Year
output$plotOptimal <- renderPlot({
# Create a Progress object
progress <- shiny::Progress$new()
progress$set(message = "Drawing plot", value = 0)
# Close the progress when this reactive exits (even if there's an error)
on.exit(progress$close())
df <- dataOptimalYear$data
labelsZ = parse(text = paste("kW/m", "^2","/year"))
with(df, {
s3d <- scatterplot3d(
tilt, azi, solar, # x y and z axis
pch = 19, # circle color indicates no. of cylinders
type = "h", lty.hplot = 2, # lines to the horizontal plane
scale.y = .75, # scale y axis (reduce by 25%)
main = "Solar Energy by Module Tilt and Azimuth angle",
xlab = "Tilt Angle (degree)",
ylab = "Module Azimuth Angle (degree)",
zlab = labelsZ,
highlight.3d = TRUE
)
s3d.coords <- s3d$xyz.convert(tilt, azi, solar)
# text(s3d.coords$x, s3d.coords$y, # x and y coordinates
# labels=row.names(df), # text to plot
# pos=4, cex=.5) # shrink text 50% and place to right of points)
# add the legend
# legend("topleft", inset=.05, # location and inset
# bty="n", cex=.5, # suppress legend box, shrink text 50%
# title="Solar Energy",
# c(">1500", "1500-1000", "1000-500","500-0"), fill=c("red", "orange","green","blue"))
fit <- lm(solar ~ tilt + azi)
s3d$plane3d(fit)
})
#Generate a summary of the optimal data
output$summaryOptimal <- renderPrint({
summary(dataOptimalYear$data)
})
# Generate an HTML table view of the optimal data
output$tableOptimal <- renderTable({
dataOptimalYear$data
})
output$textOptimal <- renderUI({
df <- dataOptimalYear$data
optimalAzi <- df$azi[df$solar == max(df$solar)][1]
optimalTilt <- df$tilt[df$solar == max(df$solar)][1]
facing <- df$fromNorth[df$azi == optimalAzi][1]
maxSolar <- max(df$solar)[1]
# withMathJax(
# "$$\\text{Total solar energy received in ", format(date, "%Y") ,": }", round(totalSolarEnergyYear$data[1], digits =
# 2) , "\\text{ }kW/m^2/year$$"
# )
withMathJax(
helpText("Optimal Tilt Angle is :$$", optimalTilt,"^o$$"),
helpText("Optimal Module Azimuth Angle is :$$",optimalAzi,"^o$$"),
helpText("The direction the module will face is:$$", facing,"$$"),
helpText(
"Maximum Solar Energy output from module according to optimal angles is:$$", round(maxSolar,digits = 2),"\\text{ }kW/m^2/year$$"
)
)
})
})
###Year Calculation###
})
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