309 lines
13 KiB
R
309 lines
13 KiB
R
#setup ----
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library(tidyverse)
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library(lubridate)
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library(httr)
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library(jsonlite)
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library(plotly)
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library(scales)
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library(readODS)
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library(ggrepel)
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setwd("~/Documents/dataProjects/ecobee")
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#make a file called 'apiKey' in your working directory that has your api key for your ecobee
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if(file.exists('authTokens.Rda')) {
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#if the authToken file already exists, then refresh it
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load(file = "authTokens.Rda")
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url <- paste0("https://api.ecobee.com/token?grant_type=refresh_token&code=",
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authTokens$refreshToken,
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"&client_id=",
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read_file('apiKey'))
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res <- content(httr::GET(url = url))
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authTokens <- data.frame(accessToken = res$access_token,
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refreshToken = res$refresh_token)
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save(authTokens, file = "authTokens.Rda")
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access_token <- authTokens$accessToken
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remove(res, url, authTokens)
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} else {
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#if the authToken file does not exist than set it up, this will require adding the app to your ecobee account
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permissions <- 'smartRead'
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url <- paste0('https://api.ecobee.com/authorize?response_type=ecobeePin&client_id=',read_file('apiKey'),'&scope=',permissions)
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res1 <- content(httr::GET(url = url))
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message(paste("add a new app to your ecobee account and authorize it with this PIN -", res1$ecobeePin))
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pause()
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url2 <- paste0("https://api.ecobee.com/token?grant_type=ecobeePin&code=",res1$code,"&client_id=",read_file('apiKey'))
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res2 <- content(httr::GET(url = url2))
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authTokens <- data.frame(accessToken = res2$access_token, refreshToken = res2$refresh_token)
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save(authTokens, file = "authTokens.Rda")
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access_token <- authTokens$accessToken
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rm(permissions, url, res1, url2, res2)
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}
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# load data ----
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startdate <- ymd('2021-11-01')
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enddate <- Sys.Date()
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columns <- c('zoneClimate',
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'compHeat1',
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'auxHeat1',
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'compCool1',
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'fan',
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'outdoorTemp',
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'outdoorHumidity',
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'zoneAveTemp',
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'zoneHeatTemp',
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'zoneCoolTemp',
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'zoneHumidity',
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'zoneHvacMode')
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months <- data.frame(start = seq(startdate, enddate, by = "month"))
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months <- months %>%
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mutate(end = start + months(1) - 1)
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ecobee <- list(NULL)
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for(i in 1:nrow(months)){
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if(file.exists(paste0('data/',months$start[i], '.Rda')) && Sys.Date() > months$end[i]){
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message(paste("Loading", months$start[[i]], "to", months$end[[i]]))
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load(file=paste0('data/',months$start[i], '.Rda'))
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} else{
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message(paste("Downloading", months$start[[i]], "to", months$end[[i]]))
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url <- paste0('https://api.ecobee.com/1/runtimeReport?format=json&body={"startDate":',
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paste0('\"',as.Date(months$start[i]),'\",'),
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'"endDate":',
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paste0('\"',as.Date(months$end[i]),'\",'),
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'"columns":',
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paste0('\"',paste0(columns, collapse = ","),'\"'),
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',"selection":{"selectionType":"thermostats","selectionMatch":"413788899054"}}')
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ecobee_month <- httr::GET(
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url = url,
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add_headers('Content-Type' = 'application/json;charset=UTF-8',
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'Authorization' = paste0('Bearer ', access_token)
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)
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) %>% httr::content()
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# parse data ----
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ecobee_month <- tibble(ecobee_month[["reportList"]][[1]][["rowList"]]) %>%
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separate(sep = ",",
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col = 1,
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into = c('date', 'time', columns),
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convert=TRUE) %>%
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mutate("duration_sec" = 5*60,
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"dateTime" = ymd_hms(paste(date, time)),
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outdoortemp_bin = round(outdoorTemp)) %>%
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filter(ymd(date) <= Sys.Date())
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if(Sys.Date() > months$end[i]){
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save(ecobee_month,
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file = paste0('data/',months$start[i], '.Rda'))
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}
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}
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ecobee[[i]] <- ecobee_month
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}
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ecobee <- bind_rows(ecobee)
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daterange <- data.frame(start = min(ecobee$date), end = max(ecobee$date))
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# import utility data ----
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utility_data <- read_ods(path = "~/Documents/1333 E 6th St/Expenses.ods", sheet = 2)
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utility_data <- utility_data %>%
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mutate(start_date = mdy(`start date`),
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end_date = mdy(`end date`))
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for(i in 1:nrow(utility_data)){
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utility_data[i, "heat_pump_hours"] <- sum(ecobee %>%
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filter(dateTime > utility_data$start_date[i],
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dateTime <= utility_data$end_date[i]) %>%
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pull(compHeat1), na.rm = TRUE)/3600
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utility_data[i, "heat_aux_hours"] <- sum(ecobee %>%
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filter(dateTime > utility_data$start_date[i],
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dateTime <= utility_data$end_date[i]) %>%
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pull(auxHeat1), na.rm = TRUE)/3600
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utility_data[i, "cool_pump_hours"] <- sum(ecobee %>%
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filter(dateTime > utility_data$start_date[i],
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dateTime <= utility_data$end_date[i]) %>%
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pull(compCool1), na.rm = TRUE)/3600
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}
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# color scale ----
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temp_types <- data.frame(column = c('zoneAveTemp', 'zoneHeatTemp', 'zoneCoolTemp', 'outdoorTemp'),
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label = c('Indoor', 'Set (heat)', 'Set (cool)', 'Outdoor'),
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color = c('black', 'orange', 'blue', 'grey'))
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equipment_types <- data.frame(column = c('compHeat1', 'auxHeat1', 'compCool1', 'fan'),
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label = c('Heat pump (heat)', 'Aux heat', 'Heat pump (cool)', 'Fan'),
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color = c('orange', 'red', 'blue', 'grey'),
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offset = c(0,1,2,3))
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equipment_y <- max(ecobee$zoneCoolTemp, ecobee$outdoorTemp, na.rm = TRUE) + 1
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# make plots ----
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ggplot() +
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geom_line(data = ecobee %>% pivot_longer(cols = c(zoneAveTemp, outdoorTemp, zoneHeatTemp, zoneCoolTemp), names_to = "temp_type", values_to = "temp"),
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aes(x = dateTime,
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y = temp,
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color = temp_type))+
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geom_rect(data = ecobee %>% pivot_longer(cols = c(compHeat1, auxHeat1, compCool1, fan), names_to = "equipment", values_to = "active_sec") %>% filter(active_sec > 0),
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aes(xmin = dateTime,
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xmax = dateTime + active_sec,
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ymin = equipment_y + equipment_types[match(equipment, equipment_types$column), 4],
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ymax = equipment_y + equipment_types[match(equipment, equipment_types$column), 4] + 1,
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fill = equipment)) +
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scale_color_manual(labels = temp_types$label, values = temp_types %>% pull(color, column)) +
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scale_fill_manual(labels = equipment_types$label, values = equipment_types %>% pull(color, column)) +
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theme(legend.title = element_blank()) +
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labs(x = 'Date',
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y = 'Temperature (\u00B0F)')
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ggsave(filename = "temp_time_all.png" ,
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path = paste(getwd(),"/figures/", sep = ""),
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device = "png",
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width = 11,
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height = 8.5,
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units = "in")
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ggplot() +
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geom_line(data = ecobee %>% filter(date > Sys.Date() - 7) %>% pivot_longer(cols = c(zoneAveTemp, outdoorTemp, zoneHeatTemp, zoneCoolTemp), names_to = "temp_type", values_to = "temp"),
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aes(x = dateTime,
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y = temp,
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color = temp_type))+
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geom_rect(data = ecobee %>% filter(date > Sys.Date() - 7) %>% pivot_longer(cols = c(compHeat1, auxHeat1, compCool1, fan), names_to = "equipment", values_to = "active_sec") %>% filter(active_sec > 0),
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aes(xmin = dateTime,
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xmax = dateTime + active_sec,
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ymin = equipment_y + equipment_types[match(equipment, equipment_types$column), 4],
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ymax = equipment_y + equipment_types[match(equipment, equipment_types$column), 4] + 1,
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fill = equipment)) +
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scale_color_manual(labels = temp_types$label, values = temp_types %>% pull(color, column)) +
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scale_fill_manual(labels = equipment_types$label, values = equipment_types %>% pull(color, column)) +
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theme(legend.title = element_blank()) +
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labs(x = 'Date',
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y = 'Temperature (\u00B0F)')
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ggsave(filename = "temp_time_last_week.png" ,
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path = paste(getwd(),"/figures/", sep = ""),
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device = "png",
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width = 11,
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height = 8.5,
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units = "in")
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ggplot(data = ecobee %>%
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filter(date != "2021-11-13",
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date != today()) %>%
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filter(zoneClimate != "") %>%
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pivot_longer(cols = c(compHeat1, auxHeat1, compCool1, fan), names_to = "equipment", values_to = "active_sec") %>%
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group_by(outdoortemp_bin, equipment, zoneClimate) %>%
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summarize(percent_active = sum(active_sec, na.rm = TRUE)/sum(duration_sec, na.rm = TRUE),
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n = n()),
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aes(x = outdoortemp_bin,
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y = percent_active,
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color = equipment,
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shape = zoneClimate)) +
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geom_point(aes(size = n)) +
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geom_smooth(aes(linetype = zoneClimate),
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se = FALSE) +
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scale_color_manual(labels = equipment_types$label, values = equipment_types %>% pull(color, column)) +
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scale_y_continuous(labels = label_percent(), expand = expansion(mult = c(0,0))) +
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labs(x = 'Outdoor Temperature (\u00B0F)',
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y = 'Percent of the time the equipment runs')
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ggsave(filename = "outdoorTemp_equipmentRun_zone.png" ,
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path = paste(getwd(),"/figures/", sep = ""),
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device = "png",
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width = 11,
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height = 8.5,
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units = "in")
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ggplot() +
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geom_col(data = ecobee %>% pivot_longer(cols = c(compHeat1, auxHeat1, compCool1), names_to = "equipment", values_to = "active_sec"),
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aes(x = as.Date(dateTime) + hours(12),
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y = active_sec/60/60,
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fill = equipment)) +
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scale_fill_manual(labels = equipment_types$label, values = equipment_types %>% pull(color, column)) +
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geom_line(data = ecobee,
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aes(x = dateTime,
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y = outdoorTemp/5,
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color = 'Outdoor')) +
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labs(x = 'date',
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y = 'Time equipment runs (hours)') +
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scale_y_continuous(sec.axis = sec_axis(trans = ~ .x*5,
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name = "Temperature (\u00B0F)"))
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ggsave(filename = "dateDay_timeRunning.png" ,
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path = paste(getwd(),"/figures/", sep = ""),
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device = "png",
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width = 11,
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height = 8.5,
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units = "in")
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ggplot() +
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geom_col(data = ecobee %>% pivot_longer(cols = c(compHeat1, auxHeat1, compCool1), names_to = "equipment", values_to = "active_sec"),
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aes(x = floor_date(dateTime, 'weeks'),
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y = active_sec/60/60,
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fill = equipment)) +
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scale_fill_manual(labels = equipment_types$label, values = equipment_types %>% pull(color, column)) +
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geom_line(data = ecobee,
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aes(x = dateTime,
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y = outdoorTemp/5*7,
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color = 'Outdoor')) +
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labs(x = 'date',
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y = 'Time equipment runs (hours)') +
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scale_y_continuous(sec.axis = sec_axis(trans = ~ .x*5/7,
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name = "Temperature (\u00B0F)"))
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ggsave(filename = "dateWeek_timeRunning.png" ,
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path = paste(getwd(),"/figures/", sep = ""),
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device = "png",
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width = 11,
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height = 8.5,
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units = "in")
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ggplot(data = ecobee %>%
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filter(date != "2021-11-13",
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date != today()) %>%
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group_by(date) %>%
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summarise(outdoorTemp = mean(outdoorTemp),
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compHeat1 = sum(compHeat1, na.rm = TRUE),
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compCool1 = sum(compCool1, na.rm = TRUE),
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auxHeat1 = sum(auxHeat1, na.rm = TRUE),
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fan = sum(fan, na.rm = TRUE)) %>%
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pivot_longer(cols = c(compHeat1, compCool1, auxHeat1, fan), names_to = 'equipment', values_to = 'active_sec') %>%
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filter(active_sec > 0),
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aes(x = outdoorTemp,
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y = active_sec/60/60,
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color = equipment)) +
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geom_point() +
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geom_smooth(se = FALSE) +
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scale_y_continuous(limits = c(0, 24), expand = expansion(mult = c(0,0))) +
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scale_color_manual(labels = equipment_types$label, values = equipment_types %>% pull(color, column)) +
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labs(x = 'Outdoor Temperature (\u00B0F)',
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y = 'Time equipment runs (hours)')
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ggsave(filename = "outdoorTemp_equipmentRun.png" ,
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path = paste(getwd(),"/figures/", sep = ""),
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device = "png",
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width = 11,
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height = 8.5,
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units = "in")
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ggplot(data = utility_data %>% filter(start_date>startdate)) +
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geom_point(aes(y = `Electricity (kWh)`,
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x = heat_pump_hours+heat_aux_hours+cool_pump_hours)) +
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geom_label_repel(aes(y = `Electricity (kWh)`,
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x = heat_pump_hours+heat_aux_hours+cool_pump_hours,
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label = `mid date`)) +
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scale_x_continuous(limits = c(0, NA), expand = expansion(mult = c(0,0.1))) +
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scale_y_continuous(limits = c(0, NA), expand = expansion(mult = c(0,0.1))) +
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labs(title = "Heat pump hours vs total kWh",
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x = "Heat Pump Hours (heating + cooling)",
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y = "Electricity (kWh)")
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ggsave(filename = "equipmentRun_electicCost.png" ,
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path = paste(getwd(),"/figures/", sep = ""),
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device = "png",
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width = 11,
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height = 8.5,
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units = "in")
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