78 lines
3.3 KiB
Plaintext
Executable File
78 lines
3.3 KiB
Plaintext
Executable File
library(dplyr)
|
|
library(dbplyr)
|
|
library(ggplot2)
|
|
library(lubridate)
|
|
library(tidyr)
|
|
|
|
# Access to our smartmeter DB
|
|
con <- DBI::dbConnect(RMariaDB::MariaDB(), host="db", dbname="smartmeter", user="root", password="rootme")
|
|
|
|
DBI::dbListTables(con)
|
|
|
|
# get some records
|
|
res <- DBI::dbSendQuery(con, "SELECT * FROM readings LIMIT 10")
|
|
DBI::dbFetch(res)
|
|
|
|
# dplyr style of reading data from mysql
|
|
# con %>% tbl("readings") %>% show_query()
|
|
|
|
# get all records from 2022
|
|
energy <- con %>% tbl("readings") %>%
|
|
select(total_m3_gas_consumed, total_kwh_consumed_high, total_kwh_consumed_low,
|
|
total_kwh_produced_high, total_kwh_produced_low, high_tarif, created_at) %>%
|
|
filter(created_at > "2021-09-01", created_at < "2021-12-31") %>%
|
|
mutate(date = as.Date(created_at)) %>%
|
|
collect()
|
|
|
|
# add hour column
|
|
energy <- energy %>% mutate(hour = format(strptime(created_at,"%Y-%m-%d %H:%M:%S"),'%H'))
|
|
|
|
# group by hour
|
|
energy_per_hour <- energy %>%
|
|
mutate(total_usage_kwh = (total_kwh_consumed_high+total_kwh_consumed_low)) %>%
|
|
mutate(total_return_kwh = (total_kwh_produced_high+total_kwh_produced_low)) %>%
|
|
group_by(date,hour) %>%
|
|
summarize(max_m3_gas_consumed = max(total_m3_gas_consumed),
|
|
min_m3_gas_consumed = min(total_m3_gas_consumed),
|
|
max_usage_kwh = max(total_usage_kwh),
|
|
min_usage_kwh = min(total_usage_kwh),
|
|
max_return_kwh = max(total_return_kwh),
|
|
min_return_kwh = min(total_return_kwh)) %>%
|
|
mutate(usage_m3 = max_m3_gas_consumed-min_m3_gas_consumed) %>%
|
|
mutate(usage_kwh = max_usage_kwh-min_usage_kwh) %>%
|
|
mutate(return_kwh = max_return_kwh-min_return_kwh) %>%
|
|
select(-max_m3_gas_consumed, -min_m3_gas_consumed, -max_usage_kwh, -min_usage_kwh, -max_return_kwh, -min_return_kwh )
|
|
|
|
# mutate(usage_kwh = round(usage_kwh,1), return_kwh = round(return_kwh,1)) %>%
|
|
# and again, group by day
|
|
energy_per_day <- energy_per_hour %>%
|
|
group_by(date) %>%
|
|
summarize(usage_m3=round(sum(usage_m3),2),
|
|
usage_kwh=round(sum(usage_kwh),2),
|
|
return_kwh=round(sum(return_kwh),2))
|
|
|
|
# some plots
|
|
energy_per_hour %>%
|
|
mutate(usage_kwh = round(usage_kwh,1), return_kwh = round(return_kwh,1)) %>%
|
|
ggplot( aes(x=date, fill=hour, y=usage_kwh, text=as.character(date))) +
|
|
geom_bar(stat="identity") +
|
|
theme_bw() +
|
|
labs(x="Date", y="kwh")
|
|
|
|
# daily usage/return of electricity
|
|
energy_per_day %>% pivot_longer(cols = usage_kwh:return_kwh) %>%
|
|
ggplot( aes(x=date, y=value, fill=name, text=as.character(date))) +
|
|
geom_bar(position="dodge", stat="identity") +
|
|
geom_text(aes(label=value), vjust=-0.3, hjust=1.2, size=2.5) +
|
|
theme_bw() +
|
|
labs(x="Date", y="kwh")
|
|
|
|
# daily usage/return of gas
|
|
energy_per_day %>% pivot_longer(cols = usage_m3) %>%
|
|
ggplot( aes(x=date, y=value, fill=name, text=as.character(date))) +
|
|
geom_bar(position="dodge", stat="identity") +
|
|
geom_text(aes(label=value), vjust=-0.3, hjust=1.2, size=2.5) +
|
|
theme_bw() +
|
|
labs(x="Date", y="m3")
|
|
|