data-raw/Examples/04 Energy Data/README.md

In JimDuggan/aimsir17: Irish Weather Observing Stations Hourly Records for 2017

Example 4 - Exploring Energy Data

R tools such as dplyr and tidyr can be used to summarise data (e.g. add rain observations to obtain monthly and annual cumulative amounts). The three libraries are first loaded.

library(aimsir17)
library(dplyr)
library(tidyr)
library(ggplot2)

We can show eirgrid’s energy data from 2017, which is recorded at 15 minute intervals.

eirgrid17

## # A tibble: 35,040 x 15
##     year month   day  hour minute date                NIGeneration NIDemand
##    <dbl> <dbl> <int> <int>  <int> <dttm>                     <dbl>    <dbl>
##  1  2017     1     1     0      0 2017-01-01 00:00:00         889.     776.
##  2  2017     1     1     0     15 2017-01-01 00:15:00         922.     770.
##  3  2017     1     1     0     30 2017-01-01 00:30:00         908.     761.
##  4  2017     1     1     0     45 2017-01-01 00:45:00         919.     743.
##  5  2017     1     1     1      0 2017-01-01 01:00:00         882.     749.
##  6  2017     1     1     1     15 2017-01-01 01:15:00         849.     742.
##  7  2017     1     1     1     30 2017-01-01 01:30:00         843.     726.
##  8  2017     1     1     1     45 2017-01-01 01:45:00         809.     709.
##  9  2017     1     1     2      0 2017-01-01 02:00:00         797.     697.
## 10  2017     1     1     2     15 2017-01-01 02:15:00         755.     684.
## # … with 35,030 more rows, and 7 more variables: NIWindAvailability <dbl>,
## #   NIWindGeneration <dbl>, IEGeneration <dbl>, IEDemand <dbl>,
## #   IEWindAvailability <dbl>, IEWindGeneration <dbl>, SNSP <chr>

The variables stored for the eirgrid data include:

glimpse(eirgrid17)

## Rows: 35,040
## Columns: 15
## $ year               <dbl> 2017, 2017, 2017, 2017, 2017, 2017, 2017, 201…
## $ month              <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
## $ day                <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
## $ hour               <int> 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, …
## $ minute             <int> 0, 15, 30, 45, 0, 15, 30, 45, 0, 15, 30, 45, …
## $ date               <dttm> 2017-01-01 00:00:00, 2017-01-01 00:15:00, 20…
## $ NIGeneration       <dbl> 889.005, 922.234, 908.122, 918.802, 882.441, …
## $ NIDemand           <dbl> 775.931, 770.233, 761.186, 742.718, 749.238, …
## $ NIWindAvailability <dbl> 175.065, 182.866, 169.796, 167.501, 174.094, …
## $ NIWindGeneration   <dbl> 198.202, 207.765, 193.103, 190.757, 195.790, …
## $ IEGeneration       <dbl> 3288.57, 3282.12, 3224.27, 3171.27, 3190.28, …
## $ IEDemand           <dbl> 2921.44, 2884.19, 2806.38, 2718.77, 2682.91, …
## $ IEWindAvailability <dbl> 1064.79, 965.60, 915.35, 895.38, 1028.03, 114…
## $ IEWindGeneration   <dbl> 1044.72, 957.74, 900.46, 870.81, 998.31, 1119…
## $ SNSP               <chr> "28.4%", "26.4%", "25.2%", "24.7%", "27.9%", …

The given energy demand for a particular day can be viewed.

mar17 <- filter(eirgrid17,day==17, month==3)
ggplot(mar17,aes(x=date,y=IEDemand))+geom_point()+geom_line()

The wind power generated for a month can be viewed

mar <- filter(eirgrid17,month==3)
ggplot(mar,aes(x=date,y=IEWindGeneration))+geom_point()+geom_line()

JimDuggan/aimsir17 documentation built on Aug. 22, 2020, 9:46 p.m.